Problem
What usually goes wrong
Demos impress; production AI fails without evals, guardrails, and clear human handoffs.
Deliverables
What you get
- Use-case selection and ROI framing
- Prototype with measurable evals
- Production integration
- Monitoring and fallback paths
- Team enablement
Process
From discovery to support
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Step 1
Discover
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Step 2
Design
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Step 3
Build
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Step 4
Launch
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Step 5
Support
Technology
Stack we ship with
Python
LLM APIs
Laravel
Queues
Vector stores
Engagement
How we work together
Spike then productize — fixed discovery, then capacity-based build.
FAQ
Questions, answered
Usually we start with strong foundation models plus retrieval. Fine-tuning only when data and ROI justify it.
Grounding, tool constraints, human review loops, and explicit refusal paths.
We design for your compliance needs — no surprise vendor data sharing.
Ready to scope this?
Book a free 20-minute call or send a brief.