AI & ML Solutions
Applied machine-learning systems that ship to production — not notebooks. Retrieval pipelines, classification, and inference infrastructure integrated into your product with the guardrails a regulated domain demands.
What you get.
- Retrieval-augmented assistants wired to your corpus
- Classification + extraction pipelines for documents
- Inference infrastructure with cost + latency budgets
- Evaluation harnesses so quality is measurable, not vibes
How we build it.
- 01
RAG with hybrid + metadata filtering
- 02
Vector stores (pgvector, dedicated)
- 03
Model orchestration + fallbacks
- 04
Prompt versioning + observability
- 05
Guardrails: PII redaction, jailbreak filters, evals
What ships.
A production AI feature with evals, monitoring, and a documented fallback path.
A four-stage delivery, start to support.
- 01
Discovery
We start with a technical architecture review, not a template. We map your domain, constraints, and the load profile the system must survive before a single line is written.
- 02
Architecture
We design the system — data models, service boundaries, security posture, and the deployment topology. You see the blueprint before the build begins, and you sign off on it.
- 03
Development
Agile sprints with weekly updates, milestone billing, and direct developer access. You watch the system being built, week by week, against the architecture we agreed on.
- 04
Launch & Support
We ship, we monitor, and we stay. Post-launch support, roadmap planning, and dedicated maintenance are part of the partnership model — not an afterthought.
Need ai & ml solutions?
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