Generative AI Development Company in Faridabad
RAG, AI agents, chatbots and document automation — built on your data and wired into the software your team already uses. We start with one workflow, prove it works with a number, then scale it.
We will tell you when a ₹2,000 tool already does what you are asking for. That happens often.
ureka.devGenerative AI Development for businesses in Faridabad
Faridabad is one of North India's oldest industrial towns — auto components, engineering and fabrication along Mathura Road and in the Sector 24–25 industrial area — alongside hospitals, schools and retail in NIT and the residential sectors. We come to your plant for discovery.
For Faridabad manufacturers: visual inspection for defects, reading drawings and purchase orders, and predictive maintenance that flags machines before they stop a line.
Areas we cover in Faridabad
- NIT Faridabad
- Sector 15–16
- Sector 24–25 industrial area
- Mathura Road
- Ballabgarh
- Sector 37
- Neharpar (Greater Faridabad)
Generative AI Development in other cities
Everyone ran an AI pilot. Almost nobody got it into daily work.
The model is not the bottleneck any more.
Someone on your team tried ChatGPT and built a demo that impressed the room. Then it met real documents, real customers and real edge cases. It was confidently wrong often enough that nobody trusted it, and it quietly stopped being opened.
Getting generative AI into daily operations is an accuracy and integration problem, not a model problem.
What we build
Agentic AI
Agents that do things — pull the record, draft the reply, update the system — not just answer questions.
Retrieval-augmented generation (RAG)
Answers grounded in your own documents, with a citation back to the source line.
Chatbots & virtual assistants
On your site, in WhatsApp, or inside your app. Handles the eleven questions your team answers every day.
Enterprise knowledge search
Staff ask one question across SOPs, contracts and policies and get the answer — not ten PDFs to read.
Document & invoice extraction
Invoices, POs, claims and KYC read, validated and pushed into your system without anyone retyping.
AI content generation
Product copy, listings, descriptions and summaries at volume, in your tone, with a human approving.
Image & video generation
Product shots, ad variants and campaign visuals without booking a studio for every version.
Personalisation & recommendations
What to show, suggest or send next, based on what this specific customer has actually done.
LLMOps & monitoringIncluded
Accuracy tracking, cost per request, prompt versioning, and an alert when quality starts drifting.
Looking for forecasting, computer vision or predictive models instead? That is AI & ML development company in Delhi.
Making it wrong less often
Generative AI projects rarely fail because the model was not clever enough. They fail because it was confidently wrong, nobody could tell when, and trust never recovered. Six things we build in from the start:
Grounded in your documents.
The model answers from your content, not from what it half-remembers from the internet.
Every answer cites its source.
A page, a clause, a document. If it cannot cite anything, it says it does not know.
A confidence threshold, not a guess.
Below the line it escalates to a person instead of inventing something plausible.
A human stays on the paths that matter.
Money, medical, legal and anything customer-facing gets reviewed until the numbers earn trust.
An evaluation set with a real number.
A few hundred real cases, scored before launch. You see the accuracy, not a promise about it.
Logged, auditable, testable for bias.
Every request and response stored, so you can answer “why did it say that” six months later.
Who this is for
Two kinds of buyer, two different problems. Find the column that sounds like you.
Product & SaaS teamsMost of our work
Your customers are asking for AI features and your engineers are already fully booked.
- SaaS teams adding the AI feature customers keep asking for
- Founders whose competitor just shipped one first
- Product teams who need an AI pod for a quarter, not a hire
Usually starts with: one feature, scoped and shipped inside your existing product.
Businesses buried in repetitive work
Your team retypes the same information and answers the same questions every single day.
- Finance and ops teams processing invoices and claims by hand
- Support teams answering the same questions all day
- Legal, insurance and healthcare teams reading long documents
- Retail and D2C brands producing endless product content
Usually starts with: one workflow — the one that eats the most hours every week.
How we work
- 01
We find the one task worth automating
Not an AI strategy. One workflow, with a number attached to how many hours it eats every week.
- 02
We check whether your data can support it
Most projects die here, before a line of code. Far better to find that out in week one than in month four.
- 03
A working prototype on your real data, usually inside two weeks
Not a slide deck and not a demo on sample data — your actual documents, your actual questions.
- 04
We score it against a real test set
A few hundred real examples, marked right or wrong. You see the accuracy number before anything goes live.
- 05
We wire it into where the work happens
Your CRM, your ERP, WhatsApp, your dashboard. Nobody adopts a tool they have to open separately.
- 06
We watch it after launch
Accuracy drifts, providers change models, costs move. We track all three and tell you before you notice.
Sometimes the honest answer is a subscription.
A large share of what businesses ask us to build is already solved by a tool that costs less per month than a single day of our time. When that is true, we will tell you which tool and how to set it up.
Custom work earns its cost when the answers have to come from your own data, run at volume inside your own software, or never leave your network.
Off-the-shelf tools
Choose this when
- — The need is general writing, summarising or research
- — The data involved is not sensitive or proprietary
- — A person reads and approves every single output
Custom buildWhere we help
Choose this when
- — Answers must come from your documents and be traceable
- — It has to run inside software you already use, at volume
- — The data cannot leave your infrastructure
Claude, GPT, Gemini, or open-weight Llama and Mistral. Python backends. Hosted on AWS, or on your own servers.
Three ways to work with us
Pilot projectRecommended
Best when nobody has proved it works yet.
One workflow, your real data, a fixed timeline, and an accuracy number at the end. Then you decide whether to go further.
How it worksFits: a first AI project, internal buy-in, getting budget approved.
Fixed-scope build
Best when the use case is already clear.
Agreed scope, fixed timeline, milestone payments. Built, integrated and handed over running.
Fits: a defined feature, a known workflow, a second project after a pilot.
Dedicated team
Best when AI is a roadmap, not a project.
A monthly pod on your product only. You set priorities, we ship every sprint.
Fits: SaaS products, ongoing AI features, teams hiring slowly.
Not sure which fits? Describe the workflow that eats the most time and we will tell you whether AI is the right tool — including when it is not.
Discuss My AI Project on WhatsAppYour data stays yours
We do not train public models on your data.
We use enterprise API tiers where the provider is contractually barred from training on your inputs.
We can run everything on your infrastructure.
Open-weight models on your own servers, so nothing ever leaves your network.
You own the model and the pipeline.
Code, prompts, fine-tuned weights and training data, in your accounts from day one.
We sign whatever you need first.
NDA before you send us a single document. Ask and it is signed the same day.
Generative AI we have shipped
Ad creative generation
An ad agency was booking a photo shoot for every product variant and every campaign. We built a Stable Diffusion pipeline trained on their own product images, so the team now generates campaign visuals in-house and only shoots what genuinely needs a camera.
See more of our workThis is the only generative AI project we can name publicly. The others are under NDA or still running. We would rather show you one real thing than five vague ones — and on a call we can talk through the work in detail, just without the client's name attached.
See more workWhy businesses work with us on AI
You own all of it.
Code, prompts, weights and data — in your name from day one.
We start small on purpose.
A pilot with a number, before anyone commits a real budget.
We tell you when it is no.
If a subscription solves it, we will say which one and how to set it up.
We build software, not demos.
Deployed, integrated and monitored — not a notebook that impressed one meeting.
Generative AI Development Company in Faridabad and across Delhi NCR
We are based in New Delhi and work with businesses across South, East, West and North Delhi, Noida, Greater Noida, Gurgaon, Ghaziabad and Faridabad, and with teams in Lucknow, Jaipur and Varanasi.
If you are in Delhi NCR, we will come and meet you. An hour on your shop floor, at your front desk or in your back office tells us more about how the business runs than a week of calls. For Lucknow, Jaipur and Varanasi, everything happens over WhatsApp and video, and we travel in for the kickoff when a project needs it.
New Delhi, India · GMT+5:30
Frequently asked questions
Yes. We meet Faridabad clients in person — NIT, the sector markets, Mathura Road, the Sector 24–25 industrial area and Ballabgarh. For plants we prefer to walk the floor before we scope anything.
The same as anywhere else we work — there is no city premium. Pricing depends on scope, and after one call you get a fixed written quote for your exact scope that does not move unless the scope does.
Cost depends on how many workflows you automate, how messy your data is, and whether it runs on your own infrastructure. Most clients start with a single fixed-price pilot on one workflow rather than committing to a full budget. After the pilot you have a real number and can decide whether to continue.
A pilot on one workflow takes four weeks. Week one is understanding the task and checking your data can support it. Weeks two and three build a working prototype on your real documents. The final week scores it against a test set so you see accuracy before deciding. See the fixed-price AI pilot
Whichever fits the task, the accuracy requirement and your privacy constraints. That may be Claude, GPT or Gemini through an API, or open-weight models like Llama or Mistral running on your own servers when data cannot leave. We pick after seeing your data, not before.
No. We use enterprise API tiers where providers contractually do not train on your inputs, or we run open-weight models entirely on your infrastructure so nothing leaves your network. We sign an NDA before you send us anything, and you own the resulting pipeline and any fine-tuned model.
Yes. WhatsApp is often the right place for it in India because customers and staff already live there. We build on the WhatsApp Business API, so the assistant answers questions, collects information and hands off to a human when it is not confident enough to reply. See our WhatsApp solutions
No. We build the monitoring, prompt versioning and dashboards so a non-technical manager can see accuracy, cost and volume without touching code. If something needs retraining or a prompt change, that sits with us under a maintenance arrangement rather than with your team.
You find out during the pilot, before committing to a full build. We score the system against a few hundred real examples and show you the number. If it cannot reach a level worth deploying, we say so and tell you what would have to change, usually better data.
Yes. Source code, prompts, pipelines, any fine-tuned model and all training data are yours from day one, in your accounts and your repositories. There is no licence back to us and no lock-in. If you stop working with us, everything keeps running exactly as it is.
That is usually the whole point. We connect to your CRM, ERP, helpdesk, database or spreadsheets through their APIs, so the output lands where people already work. Tools that live in a separate tab get abandoned within a month, however good the model is.
Tell us what your team keeps retyping
Describe the workflow that eats the most hours. We will reply with whether generative AI can do it, what a pilot would cover, roughly how long it takes, and which engagement model fits. If a subscription already solves it, we will tell you which one.
- We reply on WhatsApp within a few hours.
- A 20-minute call about how your business runs.
- A fixed written quote within 24 hours. No obligation.
Phone
Reply within a few hours on WhatsApp, fixed written quote within 24 hours. NDA signed before you send anything.
Services
Knowledge centre