Limited offerBuild your MVP in 3 days for just USD 1,799
See how it works
AI products that ship, not slide decks
We help founders and teams turn AI ideas into working products. From LLM copilots and retrieval systems to intelligent automation and custom agents, we handle model selection, evaluation, and productionisation so your users get a real experience, not a demo.
Our process & timeline
A tight, honest process built for uncertainty. We de-risk the AI part first, then engineer around what actually works.
- 011–2 days
Discovery & AI audit
We map your use case, data, and constraints. We stress-test whether AI is the right fit — and where it isn't, we say so.
- 021–2 weeks
Prototype & evaluation
We build a working prototype, choose the right models, and set up evals so quality is measurable — not vibes-based.
- 033–4 WEEKS
Build & ship
We productionise: UX, infra, observability, guardrails, and handover. You get a product your users can rely on.
FAQs
AI product development is the end-to-end process of designing, building, evaluating, and shipping software products powered by machine learning or large language models. It combines product design, data engineering, model selection, prompt and retrieval design, evaluation, and production infrastructure so users get a reliable experience — not a demo.
A working prototype usually takes 1–2 weeks. A production-ready AI product with evaluations, guardrails, observability, and a polished UX typically ships in 6–10 weeks, depending on data readiness, integrations, and scope.
We staff blended teams (design, engineering, QA, PM) from $3,300 per week. Total cost depends on scope, integrations, and how deep the AI layer is. We scope every engagement transparently before work starts so you know exactly what you're paying for.
We work with OpenAI (GPT-4/GPT-5), Anthropic Claude, Google Gemini, Meta Llama, Mistral, and open-source models via Hugging Face. We choose the model based on quality, latency, cost, and data-privacy requirements — not hype.
Yes. We build retrieval-augmented generation (RAG) systems, LLM copilots, chat interfaces, and structured extraction pipelines. We handle chunking, embeddings, vector databases (Pinecone, Weaviate, pgvector), reranking, and evaluation so answers stay grounded and accurate.
Every AI product we ship includes an evaluation harness, output guardrails, human-in-the-loop checkpoints where needed, and observability dashboards. We measure quality against real tasks continuously — not just at launch.
You own everything: code, prompts, evaluation datasets, infrastructure, and model configurations. We hand over clean repos, documentation, and knowledge transfer so your team can extend the product independently.
Book a call with Naresh
A 30‑minute discovery call with our founder. Walk through your idea, audit the fit, and leave with a clear next step, no pitch, no pressure.
"Delivered within both the deadline and the budget."
"They genuinely understand the vision and feel like part of our team."
"Hiring got faster the week we switched. The team just shipped."
"Delivered within both the deadline and the budget."
"They genuinely understand the vision and feel like part of our team."
"Hiring got faster the week we switched. The team just shipped."