A2 — AI Apps & Integration
LLM Integration (OpenAI, Anthropic)
GPT, Claude and open-source models integrated into your SaaS or internal tools, with evaluation and guardrails from day one.
Overview
Adding an LLM to a product is easy to prototype and hard to run well: answers vary, costs can surprise you, and without measurement you can't tell whether a change helped.
We integrate models such as GPT, Claude, Gemini or Llama into your product, ground them in your data, and build evaluation, guardrails and monitoring in from the start.
What we do
- 01
Choose the right model for the use case and budget
- 02
Connect the model to your product and data
- 03
Design prompts and retrieval for reliable answers
- 04
Add guardrails, logging and cost controls
- 05
Build an evaluation set and test before launch
How we work
- Step 1
Discover
We agree the use case, data sources and what a good answer looks like.
- Step 2
Build
We integrate the model, your data and your product in short iterations.
- Step 3
Evaluate
QA tests accuracy, safety and edge cases against an evaluation set before launch.
- Step 4
Monitor
We track quality and cost in production and keep improving.
Who it's for
- SaaS teams adding a first AI feature
- Teams with a prototype that isn't production-ready
- Companies adding AI to internal tools
What you get
- A model and architecture recommendation
- A production LLM integration in your codebase
- An evaluation set and pre-launch test results
- Monitoring for quality and cost
Questions
Which model should we use?+
It depends on the task, data sensitivity and budget. We often test two or three options against your own examples before recommending one.
Can we switch models later?+
Yes. We structure integrations so the model can be changed, and the evaluation set tells you whether a switch is an improvement.
What does it cost?+
Hourly work starts from $25/hr. Fixed-price projects and dedicated teams are quoted after a free scoping call, based on scope, platforms and timeline.
Tools
- OpenAI
- Claude
- Gemini
- Llama
- LangChain
- AWS Bedrock
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