AI-Powered Solutions for a Smarter, Safer World
Intelligent solutions.
Measurable impact.
Agentic AI consulting, architecture, and hands-on builds for teams shipping production systems that move metrics.
What we build
- → Agentic workflows & tool use
- → RAG & retrieval pipelines
- → Evals, monitoring, guardrails
- → Production deployment & cost
Recent thinking
From the blog
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OWASP’s LLM Top 10, through the lens of iForgetalot
Walking through the OWASP Top 10 for LLM Applications and how each item lands when your agent runs on the phone, dispatches via narrow action tags, and only falls back to a frontier API under memory pressure.
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Action tags: making an LLM actually do things
Tool use without giving the model a code interpreter. A pattern for safe, debuggable agent actions that ships in production today.
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The 70% heap rule: when to bail out of local inference
Running a quantized LLM inside a React Native app means the JS heap and the model weights are roommates. A simple memory-aware fallback prevents the crash that ruined our build 49 TestFlight release.