A generative AI studio · Richmond, KY

Light up the data you already have.

DIYAAN TECH designs and builds production-grade generative AI applications, fine-tuned models, and agentic workflows that move enterprise metrics — not just demo dashboards.

Trusted by teams shipping AI to Fortune 500 retail Top-10 US health system Public SaaS unicorn Federal civilian agency
What we do

From prompt to production.

We work the full lifecycle — problem framing, eval design, model selection, fine-tuning, deployment, guardrails, and ongoing optimization.

Custom LLM Applications

Production assistants, knowledge retrieval, document automation. Built on the right model for the job — frontier, open-weight, or hybrid.

Built for evals, not demos

Agentic Workflows

Multi-step agents that take real actions in your tools. Tight tool-use, observable trajectories, and policy-bounded autonomy.

Tool-use, planning, memory

Predictive Analytics

Forecasting, churn, segmentation, demand sensing. Classical ML where it wins, foundation models where they help.

Causal + predictive

Fine-Tuning & Distillation

Specialize open-weight models on your data. 80% of frontier quality at 5% of inference cost, on infrastructure you control.

LoRA, QLoRA, RFT

RAG & Knowledge Graphs

Retrieval pipelines that respect access control, freshness, and grounding. We design for the answer the user actually needs.

Hybrid retrieval

AI Governance

Eval harnesses, red-team programs, model cards, and audit trails. NIST AI RMF and EU AI Act-aligned.

Governance & safety

We ship evaluated AI, not vibes.

Every system we build ships with an evaluation harness measuring task accuracy, hallucination rate, latency budget, and cost-per-success. We refuse to ship before evals beat the human baseline you care about.

  • Hand-curated golden datasets per use case
  • Continuous regression evals on every model update
  • Cost-per-resolved-task tracked as a primary metric
  • Red-team battery before any production launch
"Summarize this 80-page contract and flag any clause that deviates from our playbook."
Output (4.2s, $0.012):
3 clauses flagged. Section 8.2 IP assignment is broader than playbook (impacts: customer-built derivative works). Section 11.4 limitation of liability caps at fees paid in trailing 6 months — playbook requires 12. Section 13.1 governing law is California; playbook prefers Delaware. Suggested redlines attached. Confidence: 0.94.

Have a use case in mind?

Free 60-minute scoping session. We will tell you if it is worth building — even if the answer is no.

Book a session →