TechEniac’s AI integration and automation services enable organisations to add LLM-powered features, intelligent workflow automation, and AI-driven decision-making to SaaS products already in production without disrupting your existing architecture, your users, or your deployment pipeline.
Our AI integration services go beyond basic API connections and wrapper solutions. We engineer AI as a separate service layer that connects to your existing systems via clean APIs adding intelligence where it matters most while leaving everything else intact. Production-tested across e-commerce, enterprise operations, insurance, healthcare, and financial services.
Share your product and current architecture. Our team will identify the highest-impact AI integration opportunity and provide a realistic cost estimate.
Trusted in production
AI Integration & Automation Services
TechEniac provides end-to-end AI integration services from initial assessment and architecture design through AI service development, legacy system integration, workflow automation, and production deployment.
AI integration is fundamentally different from building AI products from scratch. It operates within the constraints of your existing system your database schema, your API structure, your deployment pipeline, your user expectations. The challenge is not the AI itself. The challenge is making the AI work seamlessly within these constraints, enhancing what exists without breaking what works.
Our approach is built on a principle of minimal disruption and maximum impact. We build AI capabilities as independent service layers communicating via clean APIs. Your core codebase remains untouched. Your deployment pipeline stays intact. Your users experience new intelligent features without any disruption to workflows they already rely on.
Our AI Integration Services
Six capability areas spanning feature integration, workflow automation, legacy system connectivity, and intelligent personalisation each engineered for products already in production with real users and established workflows.
AI-powered features added to your existing product intelligent search, content generation, automated classification, predictive analytics, and natural language interfaces. Each feature is built as a separate service layer connected via APIs, ensuring your core product code remains unchanged.
BrandVoice AI integrated AI content generation into existing Shopify and WooCommerce stores product descriptions, email campaigns, and WhatsApp messages for 60+ e-commerce brands. Zero disruption to existing store operations.
Automated workflows that combine AI reasoning with system actions trigger detection, data retrieval from connected systems, AI-powered classification and decision-making, automated action execution, and human escalation when confidence is below threshold. Manual processes that took hours become automated pipelines that run in minutes.
WorkflowAI's AI Decision Nodes automate an average of 22 hours per week of operations team time per enterprise client lead qualification, risk scoring, ticket categorisation, and escalation triggers handled by AI with human oversight at configured checkpoints.
AI-powered decision-making embedded directly into business workflows. Decision Nodes receive execution context from previous steps, make structured routing decisions, log reasoning to an audit trail, and pass results to the next step. Decision types include lead qualification, compliance checking, risk scoring, content moderation, and priority routing.
WorkflowAI serves 120+ enterprise beta clients with a 97.3% workflow success rate. Every AI decision is logged with full rationale for compliance and review.
AI capabilities connected to the enterprise systems your team already uses insurance CMS platforms, healthcare EMR systems, banking APIs, e-commerce platforms, and productivity tools. Each integration is production-hardened with error handling, retry logic, rate limit management, and graceful fallback behaviour.
ClaimBot integrates with Guidewire ClaimCenter and Duck Creek Claims via REST and SOAP adapters achieving 94% CMS auto-population accuracy with configurable rate limiting, exponential backoff, and dead-letter queues for failed submissions.
AI content generation engines integrated into existing e-commerce and marketing platforms generating personalised product descriptions, email campaigns, customer communications, and social content at scale. Each integration connects to your existing product catalogue, customer data, and communication channels.
BrandVoice AI generates 1,000 product descriptions in 4 hours for 60+ brands, with a 38% increase in email open rates and 27% increase in cart recovery through AI-personalised WhatsApp messages.
AI financial analysis capabilities integrated with banking and financial data sources aggregating account data, analysing tax efficiency, modelling financial goals, and generating proactive alerts. Integrations with Open Banking, investment platforms, and pension providers create a unified financial intelligence layer.
WealthPilot AI integrates with 350+ UK banks via TrueLayer Open Banking. Average 6.2 accounts connected per user. £1,840 average annual tax savings identified per user. 2,800 active users within 3 months. NPS of 72 versus industry average of 34.
Industries We Serve
Our AI integration services are tailored to the specific system landscapes, compliance frameworks, and operational requirements of each industry.
AI content generation integrated with Shopify and WooCommerce. Product catalogue sync, personalised descriptions, email campaigns, and WhatsApp commerce messaging. Brand voice consistency across 100,000+ SKUs.
AI claims agents integrated with legacy CMS platforms (Guidewire, Duck Creek). FCA-compliant communication records generated automatically. Bidirectional data flow between AI and CMS.
AI financial analysis integrated with Open Banking (TrueLayer). Multi-account aggregation from 350+ UK banks, tax optimisation, goal modelling, and proactive financial alerts. FCA compliance boundary management.
AI decision nodes embedded in workflow platforms. Lead qualification, risk scoring, compliance checking, automated routing, and human-in-the-loop approval. 50+ connector ecosystem.
AI capabilities integrated with EMR systems via SMART on FHIR. Patient data retrieval, clinical documentation, operational coordination, and multi-facility agent orchestration.
Our Integration Approach
AI integration is a different engineering discipline than building from scratch. It requires understanding your existing architecture, respecting your deployment constraints, and delivering new capabilities without disrupting what your users depend on. Here is how we approach every integration engagement.
A comprehensive assessment of your existing architecture with a prioritised integration plan identifying the highest-impact AI integration point with the least architectural disruption.
We review your API structure, database schema, authentication system, deployment pipeline, and frontend framework. The goal is not to judge your architecture it is to understand where AI fits most naturally within it. Which workflow would benefit most? Which user pain point would AI resolve most effectively? Which integration requires the least change to deliver the most value? BrandVoice AI's assessment identified product description generation as the highest-impact integration connecting to existing Shopify product catalogues via REST API. This single integration immediately improved conversion metrics.
A production-ready AI service layer deployed independently from your core product, communicating via clean REST or GraphQL endpoints that your existing frontend and backend can consume.
We build every AI capability as a separate service deployable, updatable, and scalable independently without touching your core product code. This architectural separation ensures the AI feature can evolve rapidly without creating risk for your existing system. WorkflowAI's AI Decision Nodes were built as a separate FastAPI service. The existing workflow engine invokes the AI service at decision points, passing execution context as a structured payload. The AI returns a decision with rationale. Zero changes to the existing workflow engine just a new endpoint to call.
Production-hardened integrations connecting your AI capabilities to the enterprise systems your team already uses with error handling, retry logic, rate limit management, and graceful fallback behaviour.
Our production integration experience includes Guidewire ClaimCenter and Duck Creek Claims (REST + SOAP adapters for insurance CMS), Epic and Cerner via SMART on FHIR (healthcare EMR integration), TrueLayer Open Banking API (financial data aggregation from 350+ UK banks), Shopify and WooCommerce (e-commerce catalogue and order APIs), Google Calendar and Outlook (scheduling integration), and Meta WhatsApp Cloud API (commerce messaging). Each integration includes configurable rate limiting, exponential backoff on rate limit errors, dead-letter queues for failed operations, and monitoring dashboards for integration health. ClaimBot's Guidewire integration handles rate limit errors with exponential backoff and maintains a dead-letter queue for failed submissions production-hardened patterns that prevent integration failures from disrupting the user experience.
Automated end-to-end workflows combining AI reasoning with system actions trigger detection, data retrieval, AI processing, action execution, and human escalation all with complete audit logging.
Once the AI service layer and integrations are operational, we build automated workflows that chain these capabilities together. The automation handles trigger detection (new event, scheduled interval, or manual invocation), data retrieval from integrated systems, AI processing (classification, generation, decision-making), action execution (API calls, database updates, notification sends), and human escalation when confidence falls below threshold. WorkflowAI's entire value proposition is this pattern users define workflows on a visual canvas connecting trigger nodes, action nodes, AI decision nodes, and human approval nodes. The execution engine orchestrates these workflows asynchronously for 120+ enterprise clients with a 97.3% success rate.
The highest-impact AI integration is rarely the most obvious one. Our assessment identifies exactly where AI delivers the most measurable value within your existing product with the least architectural disruption.
Technology
High-performance async AI endpoints. Our default for AI service layers due to native async support and superior throughput for LLM orchestration tasks.
Application-layer middleware for products with existing Node.js backends. Enables AI integration without introducing a new runtime into the deployment pipeline.
LLM orchestration, prompt management, and structured output parsing.
Multi-step agent workflows for complex AI decision-making integrated into business processes.
Versioned, rate-limited endpoints. Our default integration pattern for modern systems.
Production-tested adapters for legacy enterprise systems (Guidewire, Duck Creek). Handles XML serialisation, WS-Security, and session management.
Event-driven integrations for real-time data synchronisation.
Platform authentication for Shopify, Google, Microsoft, and Open Banking providers.
Healthcare interoperability standard for EMR integration (Epic, Cerner).
Async job processing for workflow execution with configurable concurrency, retry policies, and progress tracking.
Multi-step workflows with conditional branching and parallel paths.
Failed operations captured for review and retry without blocking the pipeline.
Approval routing via Slack and email at configured decision points.
Integration request tracing across AI service calls, external API calls, and database queries.
Real-time error alerting with stack traces and breadcrumbs for integration failures.
AI performance metrics (accuracy, latency, cost per query) and integration health metrics (success rate, latency, error rate per connector).
Critical incident escalation for production integration failures.
Integration scope, legacy systems, codebase changes, performance impact the questions every founder asks before adding AI to an existing product.
Adding AI to an existing product is a different engineering challenge than building from scratch. It requires understanding your existing architecture, respecting your deployment constraints, and delivering new capabilities without disrupting what your users already depend on. That is why we start with a conversation, not a quote.