File: /var/www/html/wp-content/mu-plugins/ethnic-ai-ml-development-page.php
<?php
/**
* Plugin Name: Ethnic AI / ML Development Service Page
* Description: Creates and renders the AI / ML Development Services pillar page.
* Version: 1.0.0
*/
if ( ! defined( 'ABSPATH' ) ) {
exit;
}
if ( ! function_exists( 'ethnic_ai_ml_development_page_parent_id' ) ) {
function ethnic_ai_ml_development_page_parent_id() {
static $parent_id = null;
if ( null !== $parent_id ) {
return $parent_id;
}
$page = get_page_by_path( 'services' );
if ( $page instanceof WP_Post ) {
$parent_id = (int) $page->ID;
} else {
$fallback = get_post( 843 );
$parent_id = $fallback instanceof WP_Post ? (int) $fallback->ID : 0;
}
return $parent_id;
}
}
if ( ! function_exists( 'ethnic_ai_ml_development_page_get_target_page' ) ) {
function ethnic_ai_ml_development_page_get_target_page() {
static $page = false;
if ( false !== $page ) {
return $page instanceof WP_Post ? $page : null;
}
$page = get_page_by_path( 'services/ai-ml-development' );
if ( ! ( $page instanceof WP_Post ) ) {
$fallback = get_page_by_path( 'ai-ml-development' );
if ( $fallback instanceof WP_Post && (int) $fallback->post_parent === ethnic_ai_ml_development_page_parent_id() ) {
$page = $fallback;
}
}
return $page instanceof WP_Post ? $page : null;
}
}
if ( ! function_exists( 'ethnic_ai_ml_development_page_ensure_page' ) ) {
function ethnic_ai_ml_development_page_ensure_page() {
static $did_run = false;
if ( $did_run ) {
return;
}
$did_run = true;
$parent_id = ethnic_ai_ml_development_page_parent_id();
if ( ! $parent_id ) {
return;
}
$postarr = array(
'post_type' => 'page',
'post_title' => 'AI / ML Development Services',
'post_name' => 'ai-ml-development',
'post_parent' => $parent_id,
'post_status' => 'publish',
'post_content' => '',
'comment_status' => 'closed',
'ping_status' => 'closed',
);
$page = get_page_by_path( 'services/ai-ml-development' );
if ( $page instanceof WP_Post ) {
$needs_update = 'AI / ML Development Services' !== $page->post_title
|| (int) $page->post_parent !== $parent_id
|| 'publish' !== $page->post_status;
if ( $needs_update ) {
wp_update_post(
array_merge(
$postarr,
array(
'ID' => (int) $page->ID,
)
)
);
clean_post_cache( (int) $page->ID );
}
return;
}
$fallback = get_page_by_path( 'ai-ml-development' );
if ( $fallback instanceof WP_Post ) {
wp_update_post(
array_merge(
$postarr,
array(
'ID' => (int) $fallback->ID,
)
)
);
clean_post_cache( (int) $fallback->ID );
return;
}
wp_insert_post( $postarr );
}
add_action( 'init', 'ethnic_ai_ml_development_page_ensure_page', 5 );
}
if ( ! function_exists( 'ethnic_ai_ml_development_page_is_target' ) ) {
function ethnic_ai_ml_development_page_is_target() {
if ( is_admin() ) {
return false;
}
$page = ethnic_ai_ml_development_page_get_target_page();
if ( ! ( $page instanceof WP_Post ) ) {
return false;
}
return (int) get_queried_object_id() === (int) $page->ID || is_page( (int) $page->ID );
}
}
if ( ! function_exists( 'ethnic_ai_ml_development_page_url' ) ) {
function ethnic_ai_ml_development_page_url( $path ) {
return home_url( '/' . ltrim( (string) $path, '/' ) . '/' );
}
}
if ( ! function_exists( 'ethnic_ai_ml_development_page_contact_url' ) ) {
function ethnic_ai_ml_development_page_contact_url( $args = array() ) {
return ethnic_consultation_route_contact_url( $args, ethnic_ai_ml_development_page_url( 'contact-us' ) );
}
}
if ( ! function_exists( 'ethnic_ai_ml_development_page_case_studies_url' ) ) {
function ethnic_ai_ml_development_page_case_studies_url() {
return function_exists( 'ethnic_case_studies_archive_url' ) ? ethnic_case_studies_archive_url() : ethnic_ai_ml_development_page_url( 'case-studies' );
}
}
if ( ! function_exists( 'ethnic_ai_ml_development_page_data' ) ) {
function ethnic_ai_ml_development_page_data() {
static $data = null;
if ( null !== $data ) {
return $data;
}
$data = array(
'metaTitle' => 'AI / ML Development Services | AI Development Company & Generative AI Solutions',
'metaDescription' => 'Looking for an AI development company? We deliver machine learning development services, generative AI solutions, workflow automation, intelligent applications, and AI integrations for real business use cases.',
'heroTitle' => 'AI / ML Development Services',
'heroText' => 'We build practical AI solutions, workflow automation systems, intelligent applications, and business-ready machine learning delivery that helps teams solve operational problems, improve decisions, and create more usable digital products.',
'heroPoints' => array(
'Practical AI and machine learning solutions',
'Generative AI, automation, and intelligent workflows',
'Strategy, implementation, integration, and support',
),
'overviewParagraphs' => array(
'Our AI and machine learning development services support startups, SMBs, and enterprise teams that want real operational value from AI rather than a disconnected proof-of-concept. We focus on business problems first, then shape the right technical approach around data quality, usability, integration needs, and the way teams actually work.',
'That can include automation, prediction, classification, recommendation systems, intelligent search, copilots, knowledge assistants, document workflows, and generative AI solutions that fit into real products or internal processes. The goal is to create AI systems that make work easier, decisions faster, and experiences more useful.',
'As an AI development company, we support strategy, prototyping, development, integration, deployment, and improvement so AI delivery stays grounded in operational fit, scalability, and long-term maintainability rather than novelty alone.',
),
'overviewFeatures' => array(
array(
'icon' => 'compass',
'title' => 'Practical AI Strategy',
'copy' => 'Use-case evaluation shaped around workflow friction, measurable business value, data realities, and implementation fit.',
),
array(
'icon' => 'briefcase',
'title' => 'Use-Case-Driven Development',
'copy' => 'Solutions designed around support teams, analysts, operators, internal tools, and customer-facing experiences that need real utility.',
),
array(
'icon' => 'layers',
'title' => 'Scalable Deployment',
'copy' => 'Architecture decisions shaped around APIs, workflows, feedback loops, integrations, and dependable production delivery.',
),
array(
'icon' => 'growth',
'title' => 'Long-Term Optimization',
'copy' => 'We treat launch as the beginning of refinement, monitoring, workflow tuning, and ongoing improvement.',
),
),
'useCases' => array(
array(
'icon' => 'chat',
'title' => 'AI Chatbots and Copilots',
'copy' => 'Assist customers, agents, sales teams, or internal users with guided answers, task support, and contextual workflows.',
'url' => ethnic_ai_ml_development_page_url( 'services/ai-ml-development/ai-chatbot-development' ),
),
array(
'icon' => 'doc',
'title' => 'Document Processing and Summarization',
'copy' => 'Extract, classify, summarize, and structure information from contracts, reports, forms, or operational documents.',
),
array(
'icon' => 'spark',
'title' => 'Recommendation Systems',
'copy' => 'Improve product, content, or workflow relevance with personalized recommendations shaped around user behavior and business logic.',
),
array(
'icon' => 'chart',
'title' => 'Predictive Analytics',
'copy' => 'Support forecasting, demand signals, performance monitoring, and data-informed decision making through practical predictive models.',
),
array(
'icon' => 'search',
'title' => 'Search and Knowledge Assistants',
'copy' => 'Make internal knowledge, documentation, and business content easier to retrieve, understand, and act on.',
),
array(
'icon' => 'workflow',
'title' => 'Workflow Automation',
'copy' => 'Reduce repetitive manual steps across approvals, triage, routing, validation, and information handling processes.',
'url' => ethnic_ai_ml_development_page_url( 'services/ai-ml-development/ai-automation-services' ),
),
array(
'icon' => 'support',
'title' => 'Customer Support Automation',
'copy' => 'Support ticket handling, response assistance, self-service, knowledge lookup, and support-team productivity improvements.',
),
array(
'icon' => 'shield',
'title' => 'Anomaly Detection',
'copy' => 'Identify unusual patterns, risky events, exceptions, or operational outliers across data-driven systems and workflows.',
),
array(
'icon' => 'pen',
'title' => 'Content Generation Support',
'copy' => 'Help teams draft structured content, summaries, internal notes, or workflow outputs with the right review and control layers.',
),
array(
'icon' => 'toolbox',
'title' => 'Internal Productivity Tools',
'copy' => 'Build AI-enabled interfaces that help operations, finance, service, and delivery teams work faster with better context.',
),
),
'stackParagraphs' => array(
'The right AI and ML stack depends on the use case, available data, performance expectations, integration needs, governance requirements, and the business outcomes that matter most. We choose tools based on what is practical to operate and maintain rather than treating every project like a generic AI demo.',
'That may include hosted LLM providers, open-source models, traditional ML frameworks, retrieval pipelines, orchestration layers, API infrastructure, deployment tooling, and monitoring components based on the complexity of the system being built.',
),
'stackGroups' => array(
array(
'icon' => 'brain',
'title' => 'LLM / Generative AI',
'description' => 'Model choices depend on response quality, latency, privacy, cost, orchestration, and the type of generative AI experience required.',
'items' => array( 'OpenAI', 'Anthropic', 'Gemini', 'Open-source model options' ),
),
array(
'icon' => 'chart',
'title' => 'ML / Data Science',
'description' => 'Classic ML delivery still matters for prediction, classification, scoring, and data-driven business logic beyond LLM-centric systems.',
'items' => array( 'Python', 'scikit-learn', 'TensorFlow', 'PyTorch' ),
),
array(
'icon' => 'search',
'title' => 'Vector / Retrieval / Search',
'description' => 'Retrieval architecture supports grounded answers, knowledge access, semantic search, and more dependable AI responses.',
'items' => array( 'Vector database options', 'Embeddings', 'Retrieval pipelines', 'Semantic search workflows' ),
),
array(
'icon' => 'cloud',
'title' => 'MLOps / Deployment',
'description' => 'Production AI needs deployment, versioning, monitoring, observability, and operational controls to stay useful over time.',
'items' => array( 'Docker', 'Cloud platform options', 'API deployment', 'Monitoring tools' ),
),
array(
'icon' => 'workflow',
'title' => 'Orchestration / App Layer',
'description' => 'Business-ready AI often depends on workflow logic, retrieval, guardrails, and application layers that shape how models are used.',
'items' => array( 'Workflow tools', 'RAG pipelines', 'Agent-style architectures', 'Backend / API layers' ),
),
),
'workflowParagraphs' => array(
'AI and ML delivery depends on more than model access. The quality of data, retrieval logic, testing, feedback loops, and operational workflows often determines whether the final solution is actually useful in practice.',
'We help shape the workflow around data inputs, preparation, validation, model interaction, deployment, and improvement so the AI system fits real users, real processes, and real business constraints.',
),
'workflowSteps' => array(
array(
'title' => 'Use Case Definition',
'copy' => 'Clarify the workflow problem, business goal, user need, and success criteria before selecting models or tools.',
),
array(
'title' => 'Data Assessment',
'copy' => 'Review data availability, quality, structure, access constraints, and the operational context behind the use case.',
),
array(
'title' => 'Data Preparation',
'copy' => 'Clean, organize, label, structure, and prepare the information that will support model behavior and workflow accuracy.',
),
array(
'title' => 'Model / Workflow Selection',
'copy' => 'Choose the right model path, retrieval layer, automation logic, or ML approach based on fit rather than hype.',
),
array(
'title' => 'Integration & Testing',
'copy' => 'Connect the solution to the right systems, validate outputs, refine prompts or logic, and test against real scenarios.',
),
array(
'title' => 'Deployment',
'copy' => 'Move into production with the right APIs, app layer, controls, monitoring, and operational readiness for users.',
),
array(
'title' => 'Monitoring & Improvement',
'copy' => 'Track output quality, adoption, performance, and workflow fit so the system can keep improving after launch.',
),
),
'integrationsIntro' => 'AI tools are most valuable when they connect with the systems where work already happens. We support integrations with applications, APIs, databases, CRMs, ERPs, support systems, internal knowledge sources, and workflow tooling so AI becomes part of daily operations instead of staying isolated as a demo.',
'integrations' => array(
array(
'icon' => 'briefcase',
'title' => 'CRM / ERP Systems',
'copy' => 'Connect AI workflows with customer, order, finance, inventory, or business process systems that teams already rely on.',
),
array(
'icon' => 'book',
'title' => 'Internal Knowledge Bases',
'copy' => 'Support knowledge assistants, semantic search, and retrieval workflows across internal documentation and operational content.',
),
array(
'icon' => 'support',
'title' => 'Support Platforms',
'copy' => 'Integrate with ticketing, help desk, and support operations so AI can assist agents or improve customer self-service.',
),
array(
'icon' => 'doc',
'title' => 'Document Repositories',
'copy' => 'Connect AI systems to structured and unstructured files, forms, records, and content repositories when document intelligence matters.',
),
array(
'icon' => 'api',
'title' => 'APIs and Custom Backends',
'copy' => 'Build custom integration layers when AI needs to work with product logic, internal applications, or proprietary systems.',
),
array(
'icon' => 'chart',
'title' => 'Analytics and Reporting Tools',
'copy' => 'Support forecasting, dashboards, insight generation, and data-assisted reporting across business teams and workflows.',
),
array(
'icon' => 'chat',
'title' => 'Communication Tools',
'copy' => 'Bring AI into messaging, notifications, task routing, and collaboration channels where day-to-day work already happens.',
),
array(
'icon' => 'workflow',
'title' => 'Business Workflow Platforms',
'copy' => 'Connect approvals, automation layers, task flows, and operational systems so AI actions support real process outcomes.',
),
),
'industriesIntro' => 'AI use cases vary by industry, workflow complexity, customer expectations, compliance realities, and the kind of data environment a business operates in. We shape the solution around those operational differences rather than assuming one AI pattern fits every sector.',
'industries' => array(
array(
'icon' => 'store',
'title' => 'Retail',
'copy' => 'Support recommendations, support automation, demand insight, merchandising intelligence, and better customer-facing assistance.',
),
array(
'icon' => 'health',
'title' => 'Healthcare',
'copy' => 'Assist document handling, workflow routing, internal knowledge access, and operational support with care around complexity and process fit.',
),
array(
'icon' => 'finance',
'title' => 'Fintech',
'copy' => 'Apply AI to anomaly detection, document workflows, support tooling, customer assistance, and smarter operational visibility.',
),
array(
'icon' => 'truck',
'title' => 'Logistics',
'copy' => 'Improve routing decisions, exception handling, document processing, visibility workflows, and predictive operations support.',
),
array(
'icon' => 'education',
'title' => 'Education',
'copy' => 'Support knowledge assistants, summarization, internal tools, search experiences, and content-enabled learning workflows.',
),
array(
'icon' => 'factory',
'title' => 'Manufacturing',
'copy' => 'Help teams with anomaly detection, operational reporting, process automation, and knowledge access across complex systems.',
),
array(
'icon' => 'briefcase',
'title' => 'B2B Services',
'copy' => 'Enable proposal support, document workflows, research assistants, service automation, and internal productivity improvements.',
),
array(
'icon' => 'game',
'title' => 'Gaming / Entertainment',
'copy' => 'Support content workflows, moderation assistance, analytics, live operations, and user-facing support experiences.',
),
),
'caseStudies' => array(
array(
'title' => 'AI Knowledge Assistant for Internal Operations Teams',
'industry' => 'B2B Services',
'useCase' => 'Knowledge Assistant',
'stack' => 'RAG / LLM',
'challenge'=> 'Teams spent too much time searching across SOPs, delivery notes, and internal documentation spread across disconnected systems.',
'solution' => 'We designed a retrieval-driven assistant that surfaced more relevant answers, summaries, and process guidance inside an internal workflow layer.',
'outcome' => 'The organization gained faster information access, less manual searching, and a more practical internal support experience for day-to-day operations.',
),
array(
'title' => 'Document Processing Workflow Automation for Back-Office Operations',
'industry' => 'Fintech',
'useCase' => 'Document Intelligence',
'stack' => 'ML / Workflow Automation',
'challenge'=> 'Manual review of forms and supporting documents slowed turnaround time and created inconsistent data handling across teams.',
'solution' => 'We built a structured workflow for extraction, validation, summarization, and review routing so the right information reached the right teams faster.',
'outcome' => 'The business improved processing speed, reduced repetitive manual effort, and created a more dependable operational handoff process.',
),
array(
'title' => 'Predictive Analytics Dashboard for Demand and Operations Planning',
'industry' => 'Retail',
'useCase' => 'Predictive Analytics',
'stack' => 'Python / ML',
'challenge'=> 'Planning decisions relied on fragmented reporting and made it harder for teams to react early to demand shifts and operational changes.',
'solution' => 'We combined historical data, forecasting logic, and dashboard delivery into a clearer analytics workflow shaped around business planning decisions.',
'outcome' => 'Stakeholders gained better visibility into demand patterns, earlier operational signals, and a stronger data-assisted planning workflow.',
),
),
'faqs' => array(
array(
'question' => 'What AI and machine learning development services do you offer?',
'answer' => 'We support strategy, prototyping, custom AI applications, machine learning workflows, copilots, knowledge assistants, automation systems, predictive models, integrations, deployment, and post-launch optimization.',
),
array(
'question' => 'Can you build custom generative AI solutions for our business?',
'answer' => 'Yes. We build custom generative AI solutions around specific business workflows such as support assistance, document handling, internal knowledge access, content support, and intelligent application features.',
),
array(
'question' => 'How do you decide whether AI or ML is the right fit for a use case?',
'answer' => 'We evaluate the workflow problem, available data, output expectations, usability needs, risk, integration scope, and business value before recommending the most suitable AI, ML, or hybrid approach.',
),
array(
'question' => 'Can you integrate AI solutions with our existing systems?',
'answer' => 'Yes. Integration is a core part of delivery, including APIs, CRMs, ERPs, internal tools, support systems, data sources, and workflow platforms that make AI useful in real operations.',
),
array(
'question' => 'Do you work with internal business tools as well as customer-facing products?',
'answer' => 'Yes. We support both internal productivity use cases and customer-facing AI features depending on where the business needs the most value.',
),
array(
'question' => 'What models and platforms do you use?',
'answer' => 'The stack depends on the use case. We work with leading LLM providers, open-source options, Python-based ML tooling, retrieval systems, API layers, and deployment infrastructure selected around practical fit.',
),
array(
'question' => 'How do you handle data workflows in AI projects?',
'answer' => 'We help define the data workflow across assessment, preparation, retrieval or labeling needs, validation, model interaction, deployment, monitoring, and continuous improvement so the system works in practice.',
),
array(
'question' => 'Can you help with proof-of-concept projects before full implementation?',
'answer' => 'Yes. We can support proof-of-concept and pilot projects when a business needs to validate usability, workflow fit, technical feasibility, or ROI before a broader rollout.',
),
array(
'question' => 'Do you provide ongoing support and optimization after launch?',
'answer' => 'Yes. We support monitoring, refinement, integration updates, workflow tuning, quality improvements, and the technical support needed after launch.',
),
array(
'question' => 'Which industries do you support with AI / ML solutions?',
'answer' => 'We support a range of industries including retail, healthcare, fintech, logistics, education, manufacturing, B2B services, and entertainment-focused products where AI can solve practical workflow problems.',
),
),
'ctaTitle' => 'Looking for an AI Development Company?',
'ctaText' => 'Discuss automation opportunities, copilots, generative AI solutions, machine learning workflows, internal tools, data-driven products, or integration needs with a team focused on practical delivery rather than vague AI hype.',
'ctaHighlights' => array(
'Practical AI and machine learning development services for real workflows',
'Generative AI solutions, intelligent automation, and system integrations',
'Support across strategy, prototyping, implementation, deployment, and improvement',
),
'ctaSteps' => array(
array(
'title' => 'Share the workflow problem',
'copy' => 'Tell us about the process, product, data challenge, or AI opportunity you want to explore.',
),
array(
'title' => 'Map the right delivery approach',
'copy' => 'We help define the most suitable AI path, data workflow, integration scope, and implementation model.',
),
array(
'title' => 'Move into practical planning',
'copy' => 'Leave with clearer next steps for validation, development, integration, deployment, and long-term improvement.',
),
),
);
return $data;
}
}
if ( ! function_exists( 'ethnic_ai_ml_development_page_heading' ) ) {
function ethnic_ai_ml_development_page_heading( $eyebrow, $title, $copy = '' ) {
ob_start();
?>
<div class="ethnic-ai-ml-heading">
<?php if ( $eyebrow ) : ?>
<p class="ethnic-ai-ml-heading__eyebrow"><?php echo esc_html( $eyebrow ); ?></p>
<?php endif; ?>
<h2 class="ethnic-ai-ml-heading__title"><?php echo esc_html( $title ); ?></h2>
<?php if ( $copy ) : ?>
<p class="ethnic-ai-ml-heading__copy"><?php echo esc_html( $copy ); ?></p>
<?php endif; ?>
</div>
<?php
return ob_get_clean();
}
}
if ( ! function_exists( 'ethnic_ai_ml_development_page_icon' ) ) {
function ethnic_ai_ml_development_page_icon( $icon ) {
ob_start();
switch ( $icon ) {
case 'chat':
?>
<svg viewBox="0 0 24 24" aria-hidden="true" focusable="false">
<path d="M5 6.2h14A1.8 1.8 0 0 1 20.8 8v6.6A1.8 1.8 0 0 1 19 16.4h-7l-4.8 3.2v-3.2H5A1.8 1.8 0 0 1 3.2 14.6V8A1.8 1.8 0 0 1 5 6.2z" />
<path d="M8 10.8h8" />
<path d="M8 13.4h5.2" />
</svg>
<?php
break;
case 'doc':
?>
<svg viewBox="0 0 24 24" aria-hidden="true" focusable="false">
<path d="M7 4.2h7.2L18.8 9v10.8H7z" />
<path d="M14.2 4.2V9h4.6" />
<path d="M9.4 12h6.2" />
<path d="M9.4 15.4h5.1" />
</svg>
<?php
break;
case 'search':
?>
<svg viewBox="0 0 24 24" aria-hidden="true" focusable="false">
<circle cx="10.8" cy="10.8" r="5.8" />
<path d="m15.3 15.3 4.5 4.5" />
</svg>
<?php
break;
case 'workflow':
?>
<svg viewBox="0 0 24 24" aria-hidden="true" focusable="false">
<rect x="4" y="4.5" width="5.5" height="5.5" rx="1.2" />
<rect x="14.5" y="4.5" width="5.5" height="5.5" rx="1.2" />
<rect x="9.2" y="14" width="5.6" height="5.5" rx="1.2" />
<path d="M9.5 7.2h5" />
<path d="M12 10v4" />
</svg>
<?php
break;
case 'support':
?>
<svg viewBox="0 0 24 24" aria-hidden="true" focusable="false">
<path d="M6.2 11.2a5.8 5.8 0 1 1 11.6 0v2.4A1.8 1.8 0 0 1 16 15.4h-1.3l-2 2.2h-1.4v-2.2H8A1.8 1.8 0 0 1 6.2 13.6z" />
<path d="M9.4 11.2h5.2" />
</svg>
<?php
break;
case 'pen':
?>
<svg viewBox="0 0 24 24" aria-hidden="true" focusable="false">
<path d="m5.2 18.8 1.1-4.2L15.8 5a2 2 0 1 1 2.8 2.8l-9.6 9.5z" />
<path d="M13.8 7l3.2 3.2" />
</svg>
<?php
break;
case 'toolbox':
?>
<svg viewBox="0 0 24 24" aria-hidden="true" focusable="false">
<rect x="3.8" y="8" width="16.4" height="10.5" rx="2" />
<path d="M9 8V6.3A1.8 1.8 0 0 1 10.8 4.5h2.4A1.8 1.8 0 0 1 15 6.3V8" />
<path d="M3.8 12.2h16.4" />
<path d="M10.6 12.2v1.9h2.8v-1.9" />
</svg>
<?php
break;
case 'brain':
?>
<svg viewBox="0 0 24 24" aria-hidden="true" focusable="false">
<path d="M9.3 5.2a3.4 3.4 0 0 0-4 3.3 3.2 3.2 0 0 0 1 2.4 3.4 3.4 0 0 0 .8 5.8 3.5 3.5 0 0 0 5.7 2.5" />
<path d="M14.7 5.2a3.4 3.4 0 0 1 4 3.3 3.2 3.2 0 0 1-1 2.4 3.4 3.4 0 0 1-.8 5.8 3.5 3.5 0 0 1-5.7 2.5" />
<path d="M12 4.5v15" />
<path d="M9.4 9.2c.7.7 1.6 1 2.6 1" />
<path d="M14.6 9.2c-.7.7-1.6 1-2.6 1" />
</svg>
<?php
break;
case 'cloud':
?>
<svg viewBox="0 0 24 24" aria-hidden="true" focusable="false">
<path d="M8 18h8.5a3.7 3.7 0 0 0 .6-7.3 5.3 5.3 0 0 0-10.3 1.5A3.2 3.2 0 0 0 8 18z" />
<path d="M10.2 12.8 12 11l1.8 1.8" />
<path d="M12 11v5.2" />
</svg>
<?php
break;
case 'book':
?>
<svg viewBox="0 0 24 24" aria-hidden="true" focusable="false">
<path d="M5.2 5.2h8.2a2.3 2.3 0 0 1 2.3 2.3v11.3H7.6a2.4 2.4 0 0 0-2.4 2.4z" />
<path d="M18.8 5.2h-2.9v13.6" />
<path d="M7.8 9.2h5.3" />
</svg>
<?php
break;
case 'health':
?>
<svg viewBox="0 0 24 24" aria-hidden="true" focusable="false">
<path d="M12 20s-6.8-4.2-8.5-8.2c-1-2.3.1-5 2.5-6.1A4.9 4.9 0 0 1 12 7a4.9 4.9 0 0 1 6-1.3c2.4 1.1 3.5 3.8 2.5 6.1C18.8 15.8 12 20 12 20z" />
<path d="M12 8.7v5.8" />
<path d="M9.1 11.6h5.8" />
</svg>
<?php
break;
case 'finance':
?>
<svg viewBox="0 0 24 24" aria-hidden="true" focusable="false">
<rect x="4.2" y="6.5" width="15.6" height="11" rx="2" />
<path d="M12 9.1v5.8" />
<path d="M9.8 10.3a2.3 2.3 0 0 1 4.1-.5 2 2 0 0 1-1.1 3.7h-1.6a2 2 0 0 0-1.7 1" />
</svg>
<?php
break;
case 'education':
?>
<svg viewBox="0 0 24 24" aria-hidden="true" focusable="false">
<path d="m3.8 8 8.2-4 8.2 4-8.2 4z" />
<path d="M7 10.6v4.4c0 1.2 2.2 2.2 5 2.2s5-1 5-2.2v-4.4" />
<path d="M20.2 8v5.2" />
</svg>
<?php
break;
case 'factory':
?>
<svg viewBox="0 0 24 24" aria-hidden="true" focusable="false">
<path d="M4.2 18.8V8.9l5.2 2.6V8.9l5.2 2.6V5.2h5.2v13.6z" />
<path d="M7.2 18.8v-3.2" />
</svg>
<?php
break;
case 'game':
?>
<svg viewBox="0 0 24 24" aria-hidden="true" focusable="false">
<path d="M7.2 9.5h9.6a3.4 3.4 0 0 1 3.2 4.5l-1 3.1a2.2 2.2 0 0 1-4 .4l-1.1-1.8h-3.8L9 17.5a2.2 2.2 0 0 1-4-.4l-1-3.1a3.4 3.4 0 0 1 3.2-4.5z" />
<path d="M8 12.5h2.8" />
<path d="M9.4 11.1v2.8" />
<circle cx="15.8" cy="12.2" r="0.9" />
<circle cx="18" cy="14.2" r="0.9" />
</svg>
<?php
break;
default:
if ( function_exists( 'ethnic_ecommerce_development_page_icon' ) ) {
ob_end_clean();
return ethnic_ecommerce_development_page_icon( $icon );
}
?>
<svg viewBox="0 0 24 24" aria-hidden="true" focusable="false">
<circle cx="12" cy="12" r="8.5" />
<path d="M8.6 12.3 10.8 14.5 15.4 9.9" />
</svg>
<?php
break;
}
return ob_get_clean();
}
}
if ( ! function_exists( 'ethnic_ai_ml_development_page_render' ) ) {
function ethnic_ai_ml_development_page_render() {
$data = ethnic_ai_ml_development_page_data();
$consultation_url = ethnic_ai_ml_development_page_contact_url(
array(
'intent' => 'consultation',
'service' => 'ai-ml-development',
)
);
$team_url = ethnic_ai_ml_development_page_contact_url(
array(
'intent' => 'team',
'service' => 'ai-ml-development',
)
);
$quote_url = ethnic_ai_ml_development_page_contact_url(
array(
'intent' => 'quote',
'service' => 'ai-ml-development',
)
);
$case_studies_url = ethnic_ai_ml_development_page_case_studies_url();
$case_studies = function_exists( 'ethnic_case_studies_service_page_cards' )
? ethnic_case_studies_service_page_cards(
array(
'page_id' => get_queried_object_id(),
'limit' => 3,
'filters' => array(
'service' => array( 'ai-ml' ),
),
'fallback_items' => $data['caseStudies'],
)
)
: (array) $data['caseStudies'];
$case_studies_anchor = ! empty( $case_studies ) ? '#case-studies' : $case_studies_url;
ob_start();
?>
<div class="ethnic-ai-ml-page">
<section class="ethnic-ai-ml-section ethnic-ai-ml-section--hero">
<div class="ethnic-ai-ml-shell">
<div class="ethnic-ai-ml-hero">
<div class="ethnic-ai-ml-hero__copy">
<p class="ethnic-ai-ml-kicker">Practical AI Delivery</p>
<h1 class="ethnic-ai-ml-hero__title"><?php echo esc_html( $data['heroTitle'] ); ?></h1>
<p class="ethnic-ai-ml-hero__lead"><?php echo esc_html( $data['heroText'] ); ?></p>
<div class="ethnic-ai-ml-actions">
<a class="ethnic-ai-ml-button ethnic-ai-ml-button--primary" href="<?php echo esc_url( $consultation_url ); ?>">Book a Free Consultation</a>
<a class="ethnic-ai-ml-button ethnic-ai-ml-button--secondary" href="<?php echo esc_url( $case_studies_anchor ); ?>">View Case Studies</a>
</div>
<ul class="ethnic-ai-ml-hero__points" aria-label="AI and machine learning service highlights">
<?php foreach ( (array) $data['heroPoints'] as $point ) : ?>
<li><?php echo esc_html( $point ); ?></li>
<?php endforeach; ?>
</ul>
</div>
<div class="ethnic-ai-ml-hero__visual">
<div class="ethnic-ai-ml-visual">
<div class="ethnic-ai-ml-visual__window">
<div class="ethnic-ai-ml-visual__window-bar">
<span></span>
<span></span>
<span></span>
</div>
<div class="ethnic-ai-ml-visual__window-body">
<div class="ethnic-ai-ml-visual__nav">
<span>Assistant UI</span>
<span>Workflow</span>
<span>Model Layer</span>
</div>
<div class="ethnic-ai-ml-visual__hero-card">
<div class="ethnic-ai-ml-visual__product-shot"></div>
<div class="ethnic-ai-ml-visual__product-copy">
<span class="ethnic-ai-ml-visual__eyebrow">AI workflow mockup</span>
<strong>Business-ready assistants, automation, and model-driven applications.</strong>
<p>Practical AI interfaces built around usable outputs, data context, integrations, and operational fit rather than experimentation alone.</p>
<div class="ethnic-ai-ml-visual__tags">
<span>Copilot UX</span>
<span>Retrieval-ready</span>
<span>Workflow-aware</span>
</div>
</div>
</div>
<div class="ethnic-ai-ml-visual__catalog">
<div class="ethnic-ai-ml-visual__catalog-item">
<small>Automation panel</small>
<strong>Classification, routing, and process support</strong>
</div>
<div class="ethnic-ai-ml-visual__catalog-item">
<small>Analytics view</small>
<strong>Predictions, summaries, and operational signals</strong>
</div>
</div>
</div>
</div>
<div class="ethnic-ai-ml-visual__floating ethnic-ai-ml-visual__floating--ops">
<p class="ethnic-ai-ml-visual__floating-label">Delivery lens</p>
<strong>Use-case first, architecture second, model choice third</strong>
<div class="ethnic-ai-ml-visual__metric-row">
<div>
<small>Fit</small>
<strong>Practical</strong>
</div>
<div>
<small>Systems</small>
<strong>Connected</strong>
</div>
</div>
<div class="ethnic-ai-ml-visual__progress">
<span></span>
<span></span>
<span></span>
</div>
</div>
<div class="ethnic-ai-ml-visual__floating ethnic-ai-ml-visual__floating--checkout">
<p class="ethnic-ai-ml-visual__floating-label">Use case paths</p>
<strong>Knowledge assistants, automation, analytics, and internal productivity tools</strong>
<ul>
<li>Generative AI workflows</li>
<li>Machine learning systems</li>
<li>Integrations and deployment support</li>
</ul>
</div>
</div>
</div>
</div>
</div>
</section>
<section class="ethnic-ai-ml-section" id="overview">
<div class="ethnic-ai-ml-shell">
<?php echo ethnic_ai_ml_development_page_heading( 'AI / ML Overview', 'Machine learning development services focused on real workflow value instead of AI for AI’s sake.', 'We help businesses identify practical opportunities, build usable AI systems, connect them to the right tools, and improve them over time as workflows and data evolve.' ); // phpcs:ignore WordPress.Security.EscapeOutput.OutputNotEscaped ?>
<div class="ethnic-ai-ml-overview">
<div class="ethnic-ai-ml-prose">
<?php foreach ( (array) $data['overviewParagraphs'] as $paragraph ) : ?>
<p><?php echo esc_html( $paragraph ); ?></p>
<?php endforeach; ?>
</div>
<div class="ethnic-ai-ml-card-grid ethnic-ai-ml-card-grid--overview">
<?php foreach ( (array) $data['overviewFeatures'] as $feature ) : ?>
<article class="ethnic-ai-ml-card">
<div class="ethnic-ai-ml-card__icon">
<?php echo ethnic_ai_ml_development_page_icon( $feature['icon'] ); // phpcs:ignore WordPress.Security.EscapeOutput.OutputNotEscaped ?>
</div>
<h3><?php echo esc_html( $feature['title'] ); ?></h3>
<p><?php echo esc_html( $feature['copy'] ); ?></p>
</article>
<?php endforeach; ?>
</div>
</div>
</div>
</section>
<section class="ethnic-ai-ml-section ethnic-ai-ml-section--soft" id="use-cases">
<div class="ethnic-ai-ml-shell">
<?php echo ethnic_ai_ml_development_page_heading( 'Business Use Cases', 'Practical AI and ML applications shaped around buyer needs, team workflows, and operational outcomes.', 'These examples reflect the kinds of intelligent systems and workflow improvements businesses often invest in when they need practical automation, better information access, or more scalable decision support.' ); // phpcs:ignore WordPress.Security.EscapeOutput.OutputNotEscaped ?>
<div class="ethnic-ai-ml-card-grid ethnic-ai-ml-card-grid--use-cases">
<?php foreach ( (array) $data['useCases'] as $use_case ) : ?>
<article class="ethnic-ai-ml-card ethnic-ai-ml-card--use-case">
<div class="ethnic-ai-ml-card__icon">
<?php echo ethnic_ai_ml_development_page_icon( $use_case['icon'] ); // phpcs:ignore WordPress.Security.EscapeOutput.OutputNotEscaped ?>
</div>
<h3><?php echo esc_html( $use_case['title'] ); ?></h3>
<p><?php echo esc_html( $use_case['copy'] ); ?></p>
<?php if ( ! empty( $use_case['url'] ) ) : ?>
<a class="ethnic-ai-ml-card__link" href="<?php echo esc_url( $use_case['url'] ); ?>">Explore Service</a>
<?php endif; ?>
</article>
<?php endforeach; ?>
</div>
</div>
</section>
<section class="ethnic-ai-ml-section" id="models-tools-platforms">
<div class="ethnic-ai-ml-shell">
<?php echo ethnic_ai_ml_development_page_heading( 'Models, Tools, and Platforms', 'AI and ML stack decisions shaped around the use case, data environment, integration needs, and business goals.', 'We choose the right combination of models, ML frameworks, retrieval systems, app layers, and deployment tooling based on practical delivery needs rather than forcing every project into the same stack.' ); // phpcs:ignore WordPress.Security.EscapeOutput.OutputNotEscaped ?>
<div class="ethnic-ai-ml-prose ethnic-ai-ml-prose--narrow">
<?php foreach ( (array) $data['stackParagraphs'] as $paragraph ) : ?>
<p><?php echo esc_html( $paragraph ); ?></p>
<?php endforeach; ?>
</div>
<div class="ethnic-ai-ml-card-grid ethnic-ai-ml-card-grid--stacks">
<?php foreach ( (array) $data['stackGroups'] as $group ) : ?>
<article class="ethnic-ai-ml-card ethnic-ai-ml-card--stack">
<div class="ethnic-ai-ml-card__icon">
<?php echo ethnic_ai_ml_development_page_icon( $group['icon'] ); // phpcs:ignore WordPress.Security.EscapeOutput.OutputNotEscaped ?>
</div>
<h3><?php echo esc_html( $group['title'] ); ?></h3>
<p><?php echo esc_html( $group['description'] ); ?></p>
<ul class="ethnic-ai-ml-badge-list">
<?php foreach ( (array) $group['items'] as $item ) : ?>
<li><?php echo esc_html( $item ); ?></li>
<?php endforeach; ?>
</ul>
</article>
<?php endforeach; ?>
</div>
</div>
</section>
<section class="ethnic-ai-ml-section ethnic-ai-ml-section--soft" id="data-workflow">
<div class="ethnic-ai-ml-shell">
<div class="ethnic-ai-ml-workflow">
<div class="ethnic-ai-ml-workflow__copy">
<?php echo ethnic_ai_ml_development_page_heading( 'Data Workflow', 'AI and ML systems only become useful when data, workflow design, validation, and operations fit together.', 'We help structure the data workflow around the use case so information quality, retrieval logic, testing, deployment, and improvement are treated as part of the solution instead of afterthoughts.' ); // phpcs:ignore WordPress.Security.EscapeOutput.OutputNotEscaped ?>
<?php foreach ( (array) $data['workflowParagraphs'] as $paragraph ) : ?>
<p><?php echo esc_html( $paragraph ); ?></p>
<?php endforeach; ?>
</div>
<div class="ethnic-ai-ml-card-grid ethnic-ai-ml-card-grid--workflow">
<?php foreach ( (array) $data['workflowSteps'] as $index => $step ) : ?>
<article class="ethnic-ai-ml-card ethnic-ai-ml-card--workflow">
<span class="ethnic-ai-ml-step-number"><?php echo esc_html( sprintf( '%02d', $index + 1 ) ); ?></span>
<h3><?php echo esc_html( $step['title'] ); ?></h3>
<p><?php echo esc_html( $step['copy'] ); ?></p>
</article>
<?php endforeach; ?>
</div>
</div>
</div>
</section>
<section class="ethnic-ai-ml-section" id="integrations">
<div class="ethnic-ai-ml-shell">
<?php echo ethnic_ai_ml_development_page_heading( 'Integration Capabilities', 'AI systems become more useful when they connect to the places where teams already work.', $data['integrationsIntro'] ); // phpcs:ignore WordPress.Security.EscapeOutput.OutputNotEscaped ?>
<div class="ethnic-ai-ml-card-grid ethnic-ai-ml-card-grid--integrations">
<?php foreach ( (array) $data['integrations'] as $integration ) : ?>
<article class="ethnic-ai-ml-integration-card">
<div class="ethnic-ai-ml-card__icon">
<?php echo ethnic_ai_ml_development_page_icon( $integration['icon'] ); // phpcs:ignore WordPress.Security.EscapeOutput.OutputNotEscaped ?>
</div>
<h3><?php echo esc_html( $integration['title'] ); ?></h3>
<p><?php echo esc_html( $integration['copy'] ); ?></p>
</article>
<?php endforeach; ?>
</div>
</div>
</section>
<section class="ethnic-ai-ml-section ethnic-ai-ml-section--soft" id="industries">
<div class="ethnic-ai-ml-shell">
<?php echo ethnic_ai_ml_development_page_heading( 'Industries', 'AI and ML delivery shaped around the workflows, data environments, and operating realities of different sectors.', $data['industriesIntro'] ); // phpcs:ignore WordPress.Security.EscapeOutput.OutputNotEscaped ?>
<div class="ethnic-ai-ml-card-grid ethnic-ai-ml-card-grid--industries">
<?php foreach ( (array) $data['industries'] as $industry ) : ?>
<article class="ethnic-ai-ml-card ethnic-ai-ml-card--industry">
<div class="ethnic-ai-ml-card__icon">
<?php echo ethnic_ai_ml_development_page_icon( $industry['icon'] ); // phpcs:ignore WordPress.Security.EscapeOutput.OutputNotEscaped ?>
</div>
<h3><?php echo esc_html( $industry['title'] ); ?></h3>
<p><?php echo esc_html( $industry['copy'] ); ?></p>
</article>
<?php endforeach; ?>
</div>
</div>
</section>
<?php if ( ! empty( $case_studies ) ) : ?>
<section class="ethnic-ai-ml-section ethnic-ai-ml-section--contrast" id="case-studies">
<div class="ethnic-ai-ml-shell">
<?php echo ethnic_ai_ml_development_page_heading( 'Case Studies', 'AI delivery examples for knowledge access, document workflows, predictive systems, and practical automation.', 'These case study previews reflect the kind of AI and machine learning work we help businesses plan and implement when the goal is operational value, not AI hype.' ); // phpcs:ignore WordPress.Security.EscapeOutput.OutputNotEscaped ?>
<?php echo ethnic_shared_case_study_showcase_render( $case_studies, array( 'carousel_label' => 'AI and machine learning case studies showcase' ) ); ?>
</div>
</section>
<?php endif; ?>
<section class="ethnic-ai-ml-section" id="faq">
<div class="ethnic-ai-ml-shell ethnic-ai-ml-shell--narrow">
<?php echo ethnic_ai_ml_development_page_heading( 'FAQs', 'Answers to common questions about our AI and machine learning development services.', 'These FAQs cover generative AI, ML fit, integrations, data workflows, proof-of-concepts, and long-term support.' ); // phpcs:ignore WordPress.Security.EscapeOutput.OutputNotEscaped ?>
<div class="ethnic-ai-ml-faq">
<?php foreach ( (array) $data['faqs'] as $index => $faq ) : ?>
<details class="ethnic-ai-ml-faq__item" <?php echo 0 === $index ? 'open' : ''; ?>>
<summary>
<span><?php echo esc_html( $faq['question'] ); ?></span>
<span class="ethnic-ai-ml-faq__marker" aria-hidden="true"></span>
</summary>
<div class="ethnic-ai-ml-faq__answer">
<p><?php echo esc_html( $faq['answer'] ); ?></p>
</div>
</details>
<?php endforeach; ?>
</div>
</div>
</section>
<section class="ethnic-ai-ml-section ethnic-ai-ml-section--cta" id="cta">
<div class="ethnic-ai-ml-shell">
<div class="ethnic-ai-ml-cta">
<div class="ethnic-ai-ml-cta__copy">
<div class="ethnic-ai-ml-cta__intro">
<p class="ethnic-ai-ml-kicker ethnic-ai-ml-kicker--light">Ready to Talk</p>
<p class="ethnic-ai-ml-cta__note">Planning for intelligent workflows, ML systems, copilots, automation, and business-ready AI integration.</p>
</div>
<h2><?php echo esc_html( $data['ctaTitle'] ); ?></h2>
<p class="ethnic-ai-ml-cta__lead"><?php echo esc_html( $data['ctaText'] ); ?></p>
<div class="ethnic-ai-ml-actions">
<a class="ethnic-ai-ml-button ethnic-ai-ml-button--primary" href="<?php echo esc_url( $team_url ); ?>">Talk to Our Team</a>
<a class="ethnic-ai-ml-button ethnic-ai-ml-button--secondary" href="<?php echo esc_url( $quote_url ); ?>">Get a Free Quote</a>
</div>
<ul class="ethnic-ai-ml-cta__highlights" aria-label="AI and machine learning CTA highlights">
<?php foreach ( (array) $data['ctaHighlights'] as $highlight ) : ?>
<li><?php echo esc_html( $highlight ); ?></li>
<?php endforeach; ?>
</ul>
</div>
<aside class="ethnic-ai-ml-cta__panel" aria-label="What happens next">
<div class="ethnic-ai-ml-cta__panel-header">
<p class="ethnic-ai-ml-cta__panel-eyebrow">What Happens Next</p>
<h3 class="ethnic-ai-ml-cta__panel-title">Shape the right AI implementation plan</h3>
</div>
<ol class="ethnic-ai-ml-cta__steps">
<?php foreach ( (array) $data['ctaSteps'] as $index => $step ) : ?>
<li class="ethnic-ai-ml-cta__step">
<span class="ethnic-ai-ml-cta__step-number"><?php echo esc_html( sprintf( '%02d', $index + 1 ) ); ?></span>
<div class="ethnic-ai-ml-cta__step-copy">
<strong><?php echo esc_html( $step['title'] ); ?></strong>
<p><?php echo esc_html( $step['copy'] ); ?></p>
</div>
</li>
<?php endforeach; ?>
</ol>
<div class="ethnic-ai-ml-cta__panel-note"><strong>Focus:</strong> use-case validation, data workflow design, model and integration fit, rollout scope, and long-term improvement planning.</div>
</aside>
</div>
</div>
</section>
</div>
<?php
return ob_get_clean();
}
}
if ( ! function_exists( 'ethnic_ai_ml_development_page_styles' ) ) {
function ethnic_ai_ml_development_page_styles() {
$base_styles = '';
if ( function_exists( 'ethnic_ecommerce_development_page_styles' ) ) {
$base_styles = str_replace( 'ethnic-ecommerce', 'ethnic-ai-ml', ethnic_ecommerce_development_page_styles() );
}
return $base_styles . <<<'CSS'
.ethnic-ai-ml-page {
--ethnic-ai-ml-accent: #0f766e;
--ethnic-ai-ml-accent-dark: #115e59;
--ethnic-ai-ml-cyan: #2563eb;
--ethnic-ai-ml-lime: #d9ff9a;
}
.ethnic-ai-ml-section--hero {
background:
radial-gradient(circle at 18% 18%, rgba(15, 118, 110, 0.24), transparent 26%),
radial-gradient(circle at 84% 18%, rgba(37, 99, 235, 0.16), transparent 20%),
linear-gradient(180deg, #08141d, #102734 56%, #16374c);
}
.ethnic-ai-ml-hero__title {
max-width: 8.6ch;
}
.ethnic-ai-ml-hero__lead {
max-width: 58ch;
}
.ethnic-ai-ml-visual__window-body {
background:
radial-gradient(circle at top right, rgba(15, 118, 110, 0.18), transparent 28%),
linear-gradient(180deg, rgba(255, 255, 255, 0.96), rgba(243, 249, 249, 0.96));
}
.ethnic-ai-ml-visual__nav span,
.ethnic-ai-ml-visual__tags span {
background: rgba(15, 118, 110, 0.08);
color: var(--ethnic-ai-ml-accent-dark);
}
.ethnic-ai-ml-visual__product-shot {
background:
radial-gradient(circle at 28% 28%, rgba(255, 255, 255, 0.9), transparent 22%),
linear-gradient(150deg, rgba(15, 118, 110, 0.18), rgba(37, 99, 235, 0.08)),
linear-gradient(180deg, #effdf5, #d1fae5);
}
.ethnic-ai-ml-visual__product-shot::before {
background:
linear-gradient(180deg, #ffffff, #effcf8);
border: 1px solid rgba(15, 118, 110, 0.14);
}
.ethnic-ai-ml-visual__product-shot::after {
background: rgba(15, 118, 110, 0.12);
}
.ethnic-ai-ml-visual__eyebrow {
color: var(--ethnic-ai-ml-accent);
}
.ethnic-ai-ml-visual__floating li::before,
.ethnic-ai-ml-checklist li::before,
.ethnic-ai-ml-cta__highlights li::before {
background: var(--ethnic-ai-ml-accent);
box-shadow: 0 0 0 5px rgba(15, 118, 110, 0.12);
}
.ethnic-ai-ml-visual__floating--ops {
background:
linear-gradient(180deg, rgba(255, 255, 255, 0.08), rgba(255, 255, 255, 0.04)),
linear-gradient(180deg, #103136, #0b1f28);
}
.ethnic-ai-ml-card__icon,
.ethnic-ai-ml-platform-card__icon {
background: rgba(15, 118, 110, 0.08);
color: var(--ethnic-ai-ml-accent);
}
.ethnic-ai-ml-dashboard,
.ethnic-ai-ml-faq__marker,
.ethnic-ai-ml-dashboard__journey-step span {
background-color: rgba(15, 118, 110, 0.08);
color: var(--ethnic-ai-ml-accent);
}
.ethnic-ai-ml-dashboard {
background:
radial-gradient(circle at top right, rgba(15, 118, 110, 0.12), transparent 30%),
linear-gradient(180deg, rgba(255, 255, 255, 0.96), rgba(241, 248, 248, 0.96));
}
.ethnic-ai-ml-cta::before {
background:
linear-gradient(90deg, rgba(15, 118, 110, 0.05) 1px, transparent 1px),
linear-gradient(0deg, rgba(15, 118, 110, 0.05) 1px, transparent 1px);
}
.ethnic-ai-ml-cta .ethnic-ai-ml-kicker--light,
.ethnic-ai-ml-heading__eyebrow {
border-color: rgba(15, 118, 110, 0.16);
color: var(--ethnic-ai-ml-accent) !important;
-webkit-text-fill-color: var(--ethnic-ai-ml-accent);
}
.ethnic-ai-ml-cta .ethnic-ai-ml-kicker--light {
color: #0d6b64 !important;
-webkit-text-fill-color: #0d6b64;
box-shadow: 0 14px 36px rgba(15, 118, 110, 0.14);
}
.ethnic-ai-ml-card-grid--use-cases {
grid-template-columns: repeat(4, minmax(0, 1fr));
}
.ethnic-ai-ml-card-grid--stacks {
grid-template-columns: repeat(3, minmax(0, 1fr));
}
.ethnic-ai-ml-card-grid--workflow {
grid-template-columns: repeat(2, minmax(0, 1fr));
}
.ethnic-ai-ml-card-grid--industries {
grid-template-columns: repeat(4, minmax(0, 1fr));
}
.ethnic-ai-ml-workflow {
display: grid;
grid-template-columns: minmax(0, 0.9fr) minmax(0, 1.1fr);
gap: clamp(28px, 4vw, 48px);
align-items: start;
}
.ethnic-ai-ml-card--workflow,
.ethnic-ai-ml-card--stack,
.ethnic-ai-ml-card--industry,
.ethnic-ai-ml-card--use-case {
height: 100%;
}
.ethnic-ai-ml-card--use-case {
display: flex;
flex-direction: column;
}
.ethnic-ai-ml-step-number {
display: inline-grid;
place-items: center;
min-width: 46px;
height: 34px;
padding: 0 12px;
border-radius: 999px;
background: rgba(15, 118, 110, 0.08);
color: var(--ethnic-ai-ml-accent);
font-size: 12px;
font-weight: 800;
letter-spacing: 0.12em;
line-height: 1;
text-transform: uppercase;
}
.ethnic-ai-ml-card--workflow h3 {
margin-top: 16px;
}
.ethnic-ai-ml-badge-list {
display: flex;
flex-wrap: wrap;
gap: 10px;
padding: 0;
margin: 18px 0 0;
list-style: none;
}
.ethnic-ai-ml-badge-list li {
display: inline-flex;
align-items: center;
min-height: 32px;
padding: 7px 12px;
border-radius: 999px;
background: rgba(15, 118, 110, 0.08);
color: var(--ethnic-ai-ml-accent-dark);
font-size: 12px;
font-weight: 700;
line-height: 1;
}
.ethnic-ai-ml-card--industry p,
.ethnic-ai-ml-card--use-case p {
max-width: 34ch;
}
.ethnic-ai-ml-card__link {
display: inline-flex;
align-items: center;
gap: 8px;
margin-top: auto;
padding-top: 18px;
color: var(--ethnic-ai-ml-accent-dark);
font-size: 13px;
font-weight: 700;
line-height: 1.2;
text-decoration: none;
}
.ethnic-ai-ml-card__link::after {
content: "";
width: 8px;
height: 8px;
border-top: 2px solid currentColor;
border-right: 2px solid currentColor;
transform: rotate(45deg);
}
.ethnic-ai-ml-card__link:hover,
.ethnic-ai-ml-card__link:focus-visible {
color: var(--ethnic-ai-ml-accent);
}
.ethnic-ai-ml-card-grid--case-studies .ethnic-ai-ml-case-card {
padding: 24px;
}
.ethnic-ai-ml-case-card__tags {
display: flex;
flex-wrap: wrap;
gap: 10px;
}
.ethnic-ai-ml-case-card__tags span {
display: inline-flex;
align-items: center;
min-height: 32px;
padding: 7px 12px;
border-radius: 999px;
background: rgba(255, 255, 255, 0.08);
border: 1px solid rgba(255, 255, 255, 0.08);
color: rgba(255, 255, 255, 0.78);
font-size: 12px;
font-weight: 700;
line-height: 1;
}
.ethnic-ai-ml-case-card__summary {
display: grid;
gap: 12px;
margin-top: 18px;
}
.ethnic-ai-ml-case-card__summary p {
margin: 0;
}
.ethnic-ai-ml-integration-card,
.ethnic-ai-ml-case-card {
border-radius: 28px;
border: 1px solid var(--ethnic-ai-ml-border);
box-shadow: var(--ethnic-ai-ml-shadow);
}
.ethnic-ai-ml-integration-card {
padding: 24px;
background:
linear-gradient(180deg, rgba(255, 255, 255, 0.94), rgba(247, 250, 255, 0.96)),
var(--ethnic-ai-ml-surface-strong);
}
.ethnic-ai-ml-integration-card h3,
.ethnic-ai-ml-case-card h3 {
margin: 18px 0 0;
color: var(--ethnic-ai-ml-text);
font-family: "Plus Jakarta Sans", "Figtree", sans-serif;
font-size: 22px;
font-weight: 700;
line-height: 1.3;
}
.ethnic-ai-ml-section--contrast .ethnic-ai-ml-heading__title,
.ethnic-ai-ml-section--contrast .ethnic-ai-ml-heading__copy,
.ethnic-ai-ml-section--contrast .ethnic-ai-ml-heading__eyebrow,
.ethnic-ai-ml-case-card h3,
.ethnic-ai-ml-case-card p,
.ethnic-ai-ml-case-card strong {
color: #ffffff !important;
-webkit-text-fill-color: #ffffff;
}
.ethnic-ai-ml-case-card {
display: flex;
flex-direction: column;
gap: 16px;
height: 100%;
background:
linear-gradient(180deg, rgba(255, 255, 255, 0.08), rgba(255, 255, 255, 0.03)),
rgba(255, 255, 255, 0.02);
border-color: rgba(255, 255, 255, 0.08);
box-shadow: 0 22px 60px rgba(5, 14, 28, 0.2);
}
.ethnic-ai-ml-case-card h3 {
margin: 0;
font-size: clamp(24px, 1.9vw, 30px);
line-height: 1.16;
letter-spacing: -0.035em;
text-wrap: balance;
}
.ethnic-ai-ml-case-card__tags span {
background: rgba(255, 255, 255, 0.1);
border: 1px solid rgba(255, 255, 255, 0.12);
color: rgba(255, 255, 255, 0.92);
letter-spacing: 0.03em;
}
.ethnic-ai-ml-case-card__summary p {
color: rgba(255, 255, 255, 0.82) !important;
-webkit-text-fill-color: rgba(255, 255, 255, 0.82);
font-size: 15px;
line-height: 1.72;
}
.ethnic-ai-ml-case-card__summary strong {
color: #ffffff !important;
-webkit-text-fill-color: #ffffff;
}
.ethnic-ai-ml-case-card .ethnic-ai-ml-button--ghost {
align-self: flex-start;
margin-top: auto;
}
@media (max-width: 1200px) {
.ethnic-ai-ml-card-grid--use-cases,
.ethnic-ai-ml-card-grid--industries,
.ethnic-ai-ml-card-grid--stacks {
grid-template-columns: repeat(2, minmax(0, 1fr));
}
}
@media (max-width: 1024px) {
.ethnic-ai-ml-workflow {
grid-template-columns: 1fr;
}
}
@media (max-width: 767px) {
.ethnic-ai-ml-card-grid--use-cases,
.ethnic-ai-ml-card-grid--stacks,
.ethnic-ai-ml-card-grid--workflow,
.ethnic-ai-ml-card-grid--industries,
.ethnic-ai-ml-badge-list {
grid-template-columns: 1fr;
}
.ethnic-ai-ml-badge-list {
display: grid;
}
.ethnic-ai-ml-step-number {
min-width: 42px;
}
}
CSS;
}
}
if ( ! function_exists( 'ethnic_ai_ml_development_page_body_class' ) ) {
function ethnic_ai_ml_development_page_body_class( $classes ) {
if ( ethnic_ai_ml_development_page_is_target() ) {
$classes[] = 'ethnic-ai-ml-development-target';
}
return $classes;
}
add_filter( 'body_class', 'ethnic_ai_ml_development_page_body_class' );
}
if ( ! function_exists( 'ethnic_ai_ml_development_page_print_head_assets' ) ) {
function ethnic_ai_ml_development_page_print_head_assets() {
if ( ! ethnic_ai_ml_development_page_is_target() ) {
return;
}
$data = ethnic_ai_ml_development_page_data();
?>
<style id="ethnic-ai-ml-development-page-inline-css" type="text/css">
<?php echo ethnic_ai_ml_development_page_styles(); // phpcs:ignore WordPress.Security.EscapeOutput.OutputNotEscaped ?>
</style>
<meta name="description" content="<?php echo esc_attr( $data['metaDescription'] ); ?>" />
<?php
}
add_action( 'wp_head', 'ethnic_ai_ml_development_page_print_head_assets', 120 );
}
if ( ! function_exists( 'ethnic_ai_ml_development_page_document_title' ) ) {
function ethnic_ai_ml_development_page_document_title( $title ) {
if ( ethnic_ai_ml_development_page_is_target() ) {
$data = ethnic_ai_ml_development_page_data();
return $data['metaTitle'];
}
return $title;
}
add_filter( 'pre_get_document_title', 'ethnic_ai_ml_development_page_document_title', 50 );
}
if ( ! function_exists( 'ethnic_ai_ml_development_page_replace_content' ) ) {
function ethnic_ai_ml_development_page_replace_content( $content ) {
if ( ! ethnic_ai_ml_development_page_is_target() || ! in_the_loop() || ! is_main_query() ) {
return $content;
}
static $rendered = false;
if ( $rendered ) {
return $content;
}
$rendered = true;
return ethnic_ai_ml_development_page_render();
}
add_filter( 'the_content', 'ethnic_ai_ml_development_page_replace_content', 1000 );
}