Service
AI products that
ship safely
SaaS architecture plus pragmatic AI—guardrails, evaluation, and billing so your roadmap stays sustainable as models and traffic grow.
What we build
End-to-end product engineering for AI-native SaaS—not just a thin wrapper around a model API.
LLM features & chat UX
Streaming responses, citations, and safe defaults tuned to your domain.
RAG & knowledge bases
Chunking, embeddings, and retrieval quality you can evaluate—not guess.
Agents & workflows
Tool use with approvals, limits, and audit trails for production—not demos.
SaaS foundations
Auth, orgs, roles, usage metering, and subscriptions wired to your stack.
Safety & cost control
Built for production traffic
Prompt injection defenses, PII handling, and model routing choices that balance quality with spend—so invoices stay predictable.
Observability hooks help you trace failures, tune prompts, and prove compliance to partners and customers.
How we work with you
From feasibility spike to GA—with evidence at every step.
- 01
Use case & risk map
What must never happen, what “good” looks like, and how you’ll measure quality.
- 02
Data & evaluation
Datasets, eval harnesses, and human review loops before scaling traffic.
- 03
Build & harden
Latency budgets, fallbacks, rate limits, and logging that support incidents.
- 04
Launch & optimize
Gradual rollout, cost dashboards, and iteration from real user signals.