AI / ML Integration
AI features that survive production.
LLM integrations, retrieval pipelines and custom models — with evaluation, guardrails and a cost model, which is the part that separates a demo from a product.
What's Included
How we work.
Retrieval done properly
Chunking strategy, embedding choice, reranking and citation. Most disappointing RAG systems fail at retrieval quality, not at the model.
Evaluation before rollout
A graded evaluation set built from your real queries, so you can measure whether a prompt or model change actually improved anything.
Guardrails and failure modes
Injection handling, refusal behaviour, PII redaction and a defined answer for what the feature does when the model is wrong or the API is down.
Token cost modelled up front
Per-request cost projected against expected volume before launch, with caching and routing to smaller models where quality allows.
Deliverables
What you receive.
- Retrieval pipeline with document ingestion and reranking
- Prompt templates under version control
- Evaluation harness with a graded test set
- Guardrails: input validation, output filtering, PII handling
- Cost and latency dashboard per feature
- Fallback behaviour for model and provider outages
Engagement
$3,500 / month
Per engineer, 160 hours per month, fully dedicated. Deployed within 48 business hours, scale up or down on two weeks' notice, full IP ownership from the first commit.
FAQ
Common questions.
Which models do you work with?
Claude, OpenAI and open-weight models served on your own infrastructure. The choice follows your data residency requirements, latency budget and cost ceiling rather than fashion.
Can our data stay private?
Yes. We design for it — self-hosted embeddings, zero-retention API configurations or fully on-premise inference, depending on how strict the requirement is.
Do we need a data scientist on staff?
For LLM integration work, usually not. For custom model training on your own data, you will eventually want one, and we can work alongside them or help you scope the hire.
Other services
Get In Touch
Tell us what you are building.
Stack, team size, timeline, and what success looks like. We respond within 4 business hours on business days.
Or email info@nimlogixtechnologies.com