— AI & Automation
AIsystemsthatquietlycompoundyourteam.
LLM applications, RAG pipelines, agents, and automations — built to be observable, evaluable, and boringly reliable.
— Overview
What this engagement covers
Techbylanz designs and ships AI systems that move real business metrics — not demos. We build retrieval-augmented generation (RAG), tool-using agents, and workflow automations with evals, cost controls, and human handoffs.
We start with where AI actually helps: support deflection, knowledge search, document ops, sales assist, and internal tooling. Then we productionize with logging, guardrails, and regression tests so quality does not drift after launch.
You get a senior engineer who has shipped LLM products end-to-end — from data ingestion to admin consoles and ops runbooks.
— Benefits
Why teams pick us.
RAG done right
Chunking, retrieval, and eval harnesses that actually work.
Agents that don't drift
Guardrails, tools, and human-in-the-loop where it matters.
Evals baked in
You'll know when the model regresses before your users do.
Cost-aware
Model routing and caching so unit economics stay sane.
Private by default
PII handling, tenancy, and auditability from day one.
Integrations
Slack, HubSpot, Notion, custom — pipe AI into tools already used.
— Deliverables
What you walk away with.
- Production RAG or agent pipeline
- Eval suite with baseline scores
- Observability for prompts, retrieval, and cost
- Admin UI or ops console where needed
- Runbooks for failure modes and escalations
- Knowledge base / ingestion pipeline
— Process
How we deliver.
01
Audit
Where AI actually helps — and where it doesn't.
02
Prototype
Fast eval-driven prototypes.
03
Productionize
Guardrails, observability, cost.
04
Iterate
Continuous eval and improvement.
— Stack
Tools we ship with.
— FAQ
Common questions.
Do you fine-tune models?+
When retrieval and prompting are not enough — yes. Most wins come from better data and evals first.
Can AI stay private?+
We design for tenancy, redaction, and vendor options that match your compliance needs.
How do you measure success?+
Task success rate, citation accuracy, latency, cost per request, and business KPIs you care about.