[01.01] AI Engineering
AI that works in production.
- First prototype
- Days
- Models
- Any vendor
- Data
- Stays yours
Capabilities in AI.
01
LLM applications
Chat, search and copilots grounded in your documents and systems with retrieval-augmented generation.
02
AI agents
Tool-using agents that read, decide and act across your stack — with guardrails and human approval where it matters.
03
Workflow automation
Back-office processes — onboarding, KYC, support triage, reporting — rebuilt around AI.
04
Voice & multimodal
Speech, vision and document understanding: transcription, OCR, image and video pipelines.
05
Evaluation & guardrails
Test suites for prompts and agents, red-teaming, PII redaction, hallucination and cost monitoring.
06
Private & self-hosted
Open-weight models on your infrastructure when data can’t leave the building.
- 01.1
Our own delivery runs on agent fleets — we know where AI breaks, because we run it every day.
- 01.2
Model-agnostic: OpenAI, Anthropic, Google and open-weight models, chosen per task on quality, latency and cost.
- 01.3
Every AI feature ships with evaluations, so a model upgrade is a measured decision — not a gamble.
From first call to production.
Step 01
Use-case sprint
Pick the workflow with the clearest ROI and define how success is measured.
Step 02
Prototype
A working prototype on your real data within days.
Step 03
Harden
Evaluations, guardrails, observability and fallbacks.
Step 04
Launch & tune
Ship to users, measure, and improve quality and cost continuously.
[04] You get
Deliverables, not decks.
- Working AI product in production
- Evaluation suite & quality dashboard
- Prompt & agent documentation
- Cost and latency budgets
- Security & data-handling review
Questions, answered.
No. We use enterprise APIs with training disabled, or self-hosted models when required. Your data and prompts stay yours.
Whichever wins on your evaluation set. We benchmark several providers for quality, latency and cost, and keep the system portable so you can switch later.
Grounding in your data, constrained outputs, automated evaluations and — for high-stakes actions — human approval steps. We measure error rates instead of guessing.
Yes. Most engagements add AI features to an existing web or mobile product through APIs, without a rewrite.