AI Development · Pune, India

AI development, built in Pune.

AI products, agents and automation for companies in Pune and beyond, built where intelligence genuinely earns its place, not bolted on for the pitch deck.

AI that ships inside a real product, not a demo.

Most AI work in the market stops at a proof of concept. Ours starts there and goes all the way to a working capability inside your product, measured against real usage.

Because the same team designs and engineers the whole thing, the AI is wired into the product properly: the part everyone else leaves you holding.

What we build

AI agents & copilots

Task-running agents and in-product copilots that do real work, with guardrails you can trust.

Tool useGuardrailsEvals

RAG & knowledge systems

Retrieval over your own data so answers are grounded, current and defensible.

RetrievalVector searchGrounding

LLM integration

Model selection, prompt systems and pipelines wired into your existing stack.

PipelinesPrompt systemsAPIs

Workflow automation

The manual step, the copy-paste, the thing eating your team's week, automated end to end.

AutomationIntegrationsOps

When AI earns its place

The manual step that eats a week

The copy-paste between tools, the triage, the first draft a person then edits. Automating the boring middle is where AI pays for itself quietly.

Answers from your own data

Retrieval over your documents, tickets or catalogue, so answers are grounded, current and defensible instead of a general model guessing.

An AI-native product

When the AI is the product, the first sentence it says is the experience. That has to be designed as carefully as any screen.

Throughput your team cannot reach

Work that is repeatable and checkable at volume: summarising, classifying, drafting, routing, where a human reviews instead of produces.

Where we will tell you no

  • A chat bubble added so the landing page can say AI.
  • A flow that must be right every time, where a wrong answer would pass unnoticed. There we put a human gate in front, or we do not use AI at all.
  • A problem that a clean form, a better workflow or a plain database query already solves.
How it worksOne team
01

Position

We start with the one decision that shapes everything downstream, not a feature list.

02

Design

Identity, product UX and a system built to be engineered against, not filed away.

03

Build

Full-stack engineering, with the hard integration handled by the people who designed it.

04

Ship

Launch with SEO, analytics and performance baked in, and a handover that actually works.

Why founders trust us with AI

We have shipped AI into production products, not slide decks. The proof is depth of craft at a fidelity most shops avoid because they cannot match it.

  • 01 TechShorts: brand, full-stack platform and an AI pipeline shipped in four weeks.
  • 02 Everwed: an AI product built into a full-stack platform, not layered on top.
  • 03 Blown Diffuser: a custom agent pipeline feeding a live newsroom.

AI development, in plain English

What is a RAG system?

Retrieval-augmented generation (RAG) means the model looks things up before it answers. Your documents are split into passages and indexed, the passages most relevant to a question are retrieved, and the model answers from those passages rather than from memory.

It is the difference between an assistant that sounds plausible and one that can show where its answer came from. For most businesses it is the most useful AI system to build first.

Agent, copilot or automation?

An automation runs the same steps every time. A copilot sits inside a product and helps a person do their work faster. An agent is given a goal and a set of tools and decides the steps itself.

More autonomy means more to guard. We pick the least autonomous shape that solves the problem, then add evaluation, logging and guardrails in proportion to what is at stake.

Which model should we use?

It depends on the job: quality of reasoning, speed, cost per call, and where the data is allowed to go. We have shipped on Anthropic Claude and on Llama models served by Groq, and we choose per task rather than by habit.

We design so the model can be swapped later. Prices and capabilities move every quarter; your product should not have to be rebuilt when they do.

How do you keep AI cost under control?

By caching what does not need regenerating, using smaller models where they are good enough, and doing the expensive call once rather than on every page view. On TechShorts, summaries are generated once and cached permanently, so AI cost does not scale with traffic.

What we build it withShipped, not listed
Anthropic ClaudeEverwed's planning assistant
Llama 3.1 70B on GroqTechShorts' 60-word summaries
Supabase (Postgres)Data layer for Everwed, TechShorts and CR News
Next.jsThe product surface around the AI
SentryMonitoring on TechShorts and CR News
ResendTransactional email on TechShorts and Kaien
Investment

What AI development costs

₹1,00,000

Custom engagements start here

Custom engagements start at ₹1,00,000. We publish the floor so the conversation starts honestly, and the final number scales with scope.

What moves it: how many distinct user roles and flows there are, how many systems it has to talk to, whether there is AI in the loop and how much it has to be trusted, and how much brand and design work comes before the build.

Not sure what you need yet? The fixed-fee AI Opportunity Audit sizes it first, and the full breakdown of how we price lives in the pricing guide.

Where we work

AI development, made in Pune

We are a Pune studio, close enough to sit across the table from founders in Baner, Kalyani Nagar, Koregaon Park and Hinjewadi, and remote enough to ship for teams well beyond the city.

Local when it helps, borderless when it counts. The bar is the same either way: work that competes anywhere, made by people you can actually reach.

Questions
What kind of AI projects do you take on?
Agents and copilots, retrieval systems over your own data, LLM integration into an existing product, and workflow automation. If AI does not genuinely help, we will tell you that too.
Do you build AI into an existing product or from scratch?
Both. We work inside your current stack when that is right, or design and build the whole product when the AI is the point of it.
How fast can you ship?
Fast: TechShorts went from nothing to brand, platform and an AI pipeline in four weeks. Most engagements run a few weeks to a few months by scope.
Do you work with companies outside Pune?
Yes. We are based in Pune and love local founders, but a good share of what we ship is for teams elsewhere in India and overseas.
What does an AI project cost?
Custom engagements start at ₹1,00,000 and scale with scope. If you are not ready for a full build, the fixed-fee AI Opportunity Audit is the cheapest way to start.
What is the AI Opportunity Audit?
A fixed-fee, one-to-two week engagement at ₹51,000. We map where AI genuinely earns its place in your business, score each opportunity by effort and impact, and hand you a costed build plan you can act on, with us or without.
What happens when the AI gets something wrong?
We design for it before we ship. For every AI step we ask what happens on the answer it gets wrong, and where a wrong answer would pass unnoticed we put a human review in front of it or do not use AI there at all.

Let's build.

Projects from ₹1,00,000 · or start with the ₹51,000 AI Audit

Send a brief →Book the AI Audit