AI Development / AI integration & support
AI integration into the systems you already run.
We connect AI to your data, tools and workflows, then keep it monitored, tuned and supported in production.
Astra Short on time? Ask about this page in plain words.
AI integration services. AI that fits into your stack, and stays working.
Integration assessment
Find where AI fits into your current systems and data.
API & data integration
Connect models to the systems that hold your data.
AI in existing products
Add AI features to a product you already run.
Data consolidation
Bring siloed data into one connected workflow, as we did for an insurance broker.
Role-based access & audit trails
Control who sees what, and log every record change.
Monitoring
Track quality, cost and failures once AI runs in production.
Ongoing tuning
Adjust prompts, models and rules as your data changes.
Model upgrades
Swap or upgrade models without rebuilding the product.
Support & maintenance
A defined support window and a team that knows the system.
Integrated AI we have shipped. Each result comes from a delivered engagement.
Full-stack AI platform for insurance
Fragmented policy, claims and correspondence data connected into one structured workflow.
~2.5x faster processing AI · Agent platformsAI agent platform
Agents retrieve, reason and act across systems, with human approval before high-stakes actions.
~40% less manual effort AI · Document intelligenceAI document intelligence
Extraction and classification that sends only the exceptions to people.
>80% less manual reviewIs your data split across disconnected tools?
From idea to production. Four stages, with a working version reviewed at each one.
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Discovery
Map the current setup, the systems and data involved, and what good looks like.
Discovery notes
- Current systems and data flows
- Where AI adds value
- Constraints and access rules
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Scope & architecture
Agree the architecture, success measures and delivery milestones.
Solution design
- Integration architecture
- Access and audit design
- Delivery milestones
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Build
Build against real data, with a working version reviewed at each milestone.
Working build
- Integrations built and tested
- Quality checked on real data
- Review at each milestone
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Ship & support
Roll out to production with monitoring and a defined support window.
Production rollout
- Production rollout
- Monitoring and alerts
- Ongoing support
Why Avinya for AI integration. AI that fits the systems you already run.
Works in your tools
Connected into the systems your team already uses, not a separate app to learn.
People stay in control
Approval checkpoints, escalation paths and exception review are designed in from day one.
Traceable by default
Citations, audit trails and logs, so outputs can be verified rather than trusted blindly.
Production, not demos
Built to run against real systems and real data, with monitoring once live.
Full-stack delivery
Data pipelines, models, product and integrations from one team.
AI and Web3 under one team
One studio for AI systems and, where it helps, on-chain infrastructure.
Results from our integration work. Each number links to the engagement it came from.
Engagement models. Pick the shape that fits where you are.
Dedicated team
A dedicated team that works as an extension of yours, from first release to scale.
Project-based
A defined scope, milestones and delivery date for a specific product or workflow.
Consulting & advisory
Architecture and readiness advice before you commit to a build.
What our clients say.
“Avinya Labs built our full-stack AI solution, delivering scalable infrastructure, optimized AI workflows, and a seamless user experience. Their expertise accelerated our launch and significantly reduced execution risk.”
“Avinya Labs built our AI travel chatbot … A highly capable team that delivers ahead of the curve.”
Guides on this topic. Plain answers to the questions buyers ask first.
Enterprise AI Deployment: Why Projects Stall in Pilot
The eight causes we see most, and a roadmap that gets AI live.
Read the guide → GuideOperational AI Systems: A 2026 Guide for Enterprises
How AI moves from pilots into the daily operations of a business.
Read the guide → GuideHow to Build a RAG System for Your Company Knowledge Base
Architecture, components and stack choices, and when RAG is the wrong tool.
Read the guide →AI integration FAQs.
Can you add AI to our existing product?
Yes. We integrate through your APIs and data sources, working alongside your team or end to end.
What does ongoing support include?
Monitoring, tuning as data changes, model upgrades and fixes, within a support window we agree up front.
Can we change AI models later?
Yes. We design the integration so models can be swapped without rebuilding the product.
How do you handle our data?
Access is scoped to what the system needs, with role-based permissions and audit trails where records change. We agree data handling during discovery.
How long does a project take?
It depends on scope and integrations. We agree milestones up front and review a working version at each one.
What does AI integration services work involve?
Connecting AI to your existing systems through documented APIs, with permissions, logging and a fallback if the model is unavailable. Our AI integration services keep your systems of record in charge and follow the NIST AI Risk Management Framework for risk.
Free tool
How ready is your business for AI?
Twenty questions, about four minutes. You get a score across five areas and what to fix first.