Service
AI Integration
We wire large language models into the systems you already run — support, sales, operations — so the model does the repetitive reasoning and a named human owns the exceptions.
What an integration contains
01
Use-case selection
We start from your highest-volume repetitive decision, not the flashiest demo.
02
Prompt & context design
The model gets exactly the context it needs — no more, so it stays predictable.
03
Tool & data wiring
Read and write access to the systems it needs to act in, scoped tightly.
04
Guardrails
Validation, rate limits and a clear boundary on what the model is allowed to decide alone.
05
Evaluation
A test set you can rerun on every change, so quality is measured, not assumed.
06
Handover
Documentation, runbooks, and a monitoring dashboard your team actually reads.
Guardrails
Every integration ships with the same non-negotiables, regardless of use case.
- Human escalation
- A clear, tested path to a person for anything outside scope.
- Audit trail
- Every model decision logged and attributable.
- Rate limits
- Hard ceilings on cost and call volume, enforced in code.
- Data boundary
- The model only sees what the task in front of it requires.
- Kill switch
- One command to disable the integration without a deploy.