AI Integration Services
Most companies don’t need a new AI product. They need the software they already have to do more: search that understands a question, a summary of a long customer record, a draft reply waiting for the support team. We add AI features and automation to your existing product, tools and operations, connected to your own data, with validated outputs and monitoring so the feature behaves predictably for customers and staff.
What this gives you
- AI features inside your current product, without a rebuild
- Connected to your own data and existing access permissions
- Model costs tracked and kept predictable as usage grows
Some of the teams we’ve worked with
What’s included
The work we take responsibility for.
AI features in your product
Assistants, semantic search, summarization, recommendations and smart automation built into your existing app and interface.
LLM integration
OpenAI, Anthropic and AWS Bedrock models connected through your existing backend, with structured outputs validated before they’re used.
RAG on your data
Answers drawn from your documents and databases, following the same access rules as the rest of your system, with sources shown.
Automation in internal tools
AI steps added to processes your staff already follow, such as classifying incoming requests or extracting data from documents.
Testing and monitoring
Evaluations on real examples, guardrails and monitoring, so quality holds as usage grows.
Cost and model strategy
The right model for each task, with caching, limits and usage tracking so the monthly bill doesn’t come as a surprise.
Deliverables
What you keep when the work is done.
- Integration plan and expected benefits
- AI features in production
- Data and system connections
- Guardrails and monitoring
- Documentation and handover
How we deliver
Scope and design the system
A senior engineer works out the data model, the integrations and the build plan with you. These decisions shape everything after, so a person makes them.
Build, with AI on the routine work
AI tools draft scaffolding, boilerplate and first-pass tests, so engineering hours go into the parts specific to your business.
Review and harden
Engineers review the code, check security and own the quality of what ships. Nothing AI-drafted goes out unreviewed.
Launch and keep improving
Production release with monitoring in place, then short cycles of changes based on how people actually use it.
FAQ
Common questions about AI Integration
What are AI integration services?
Adding AI to the software and processes you already run, rather than building something new: assistants, search, summaries and automation connected to your data, built to production standards with testing and monitoring.
How is this different from AI development?
AI development builds a new AI product or system; AI integration adds AI to what you already have. Many clients start with integration, one useful feature in the current product, because it shows value without a rebuild and tells you how users respond.
How do you keep AI reliable in production?
We ground the model in your data, validate outputs before they’re used, test against real examples and monitor quality after launch. Where a wrong answer would be costly, a person reviews the output before it goes anywhere.
Which models do you integrate?
Whichever fits the task: OpenAI, Anthropic (Claude) or models on AWS Bedrock, chosen on quality, cost and response time. We build the integration so the model can be changed later without reworking your product.
What happens to our data?
We start by mapping what data each feature needs and where it will be sent. OpenAI and Anthropic both state that, by default, they don’t train models on data sent through their business APIs, but you should still check this against your own contracts and obligations. We also design access controls so the AI only sees what the user is allowed to see.
Related services
Talk through what you need with someone technical.
Share a few details and an engineer will reply within one business day with clear next steps. If it looks like a fit, you can start with a one-week trial on real work.