AI Engineering

AI that ships.
Not AI that demos.

LLM integration, AI agents, RAG, multi-model cross-validation pipelines. We build AI that holds up in production — because we run AI in production every day across our own products.

From LLM call to AI product.

Six things we build with AI.

Conversational AI

Chat assistants, customer-support agents, voice-mode products. Built with prompt versioning, content moderation, and rate limiting from day one.

AI Agents

Multi-step workflows that take actions, not just answer questions. Tool use, structured output, fallback chains, observability.

RAG Systems

Retrieval-augmented generation over your docs, knowledge base, or proprietary data. Vector DB, hybrid search, citation enforcement.

Cross-Validation Pipelines

Producer-reviewer architectures: every output reviewed by a second model before delivery. Catches hallucinations and ungrounded claims. We use this on our own products.

Eval Harnesses

Test datasets, scoring rubrics, regression detection on prompt changes. The discipline that turns "vibes" into measurable AI quality.

Productivity Automation

Replace manual workflows with AI agents — document processing, classification, drafting, research. Hours of work become seconds of compute.

What sets us apart

We've shipped AI
in production. Repeatedly.

AI Essay Grader runs rubric-aligned grading at scale. Astro Yagya answers chart-specific questions in seconds. Both live in production with paying users. Both are wired with the same patterns we'll build into your system.

  • Multi-provider abstraction — swap Claude, GPT-4, Gemini without rewrites
  • Cost guards and budget caps so AI spend stays predictable
  • Response caching that quietly saves you 30-60% of LLM costs
  • Cross-model validation — the "second-opinion" pattern that catches hallucinations

Wire AI into your business?

A chatbot, an agent that takes actions, or replacing a manual process with an LLM pipeline — let's scope it.

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