Knowledge assistants (RAG)
Answers drawn from your manuals, policies, contracts and past tickets, with the source cited so staff can check it.
Service · AI solutions
AI solutions and AI development services
Production AI built on your own data: knowledge assistants, document processing, forecasting and LLM features inside the tools your team already uses. We put AI where it removes work, not where it looks impressive in a deck.
- Start with
- A proof of valueOn your real data
- Accuracy
- Grounded answersWith human hand-off
- Models
- Chosen per taskHosted APIs or open-weight
- Your data
- Handling agreed in writingBefore the build starts
- Stack
- Python, LangChain, RAGVector databases, custom ML
01 — What we build
AI that removes work
The best first AI projects are repetitive, high-volume tasks with clear right answers. These are the ones we build most.
Document AI
Purchase orders, invoices, bills of lading, KYC documents and forms read, extracted and keyed into your systems, with low-confidence fields flagged for review.
LLM features in your product
Search, summarisation, drafting and copilots inside your SaaS or internal tools, built with evaluation and cost controls.
Forecasting & analytics
Demand forecasts, reorder suggestions, payment-risk scores and plain-language questions over your business data.
Conversational AI
Assistants on WhatsApp and the web that answer in the customer's language and hand off to people when needed.
Generative imagery
Product images and catalogue content at scale; our JewelShoot turns one jewellery photo into on-model shots in under a minute.
AI agents
When the job is to act, not just answer: agents that take orders, chase payments and update your ERP. See AI agent development.
Not sure where AI fits?
Bring us the task your team hates most. We will tell you honestly whether AI is the answer.
Ask us02 — Accuracy
How we keep AI accurate
An AI system is only useful if people can trust it. These are non-negotiable on every build.
- Grounding: the model answers from your approved documents and data using retrieval-augmented generation (RAG), not from memory.
- Scope limits: each assistant has a defined job and is built to refuse rather than guess when a question falls outside it.
- Evaluation sets: we test against real questions from your business before launch and after every change.
- Human hand-off: anything high-stakes or uncertain goes to a person, with the context attached.
- Logging: every conversation and output is logged, so you can audit what the system said and why.
03 — Models & data
Choosing models and keeping data safe
We pick the model for the task, not the other way round: commercial APIs from the major providers where quality matters most, and smaller or open-weight models you can host yourself where cost, speed or data residency matter more. Many systems use both.
Your documents are indexed in a vector database you control, access follows the same roles as the rest of your systems, and what may be sent to a third-party model is agreed in writing before the build starts. Where regulation applies, such as GDPR and the EU AI Act in Europe or India's DPDP Act, we design for it from the start rather than retrofit it.
04 — Process
From idea to production AI
01
Find the use case
Repetitive, high-volume work with clear right answers makes the best first project.
02
Prove value
A small proof of value on your real data, measured against how the work is done today.
03
Build for production
Integration with your systems, permissions, monitoring and cost controls.
04
Launch with people
Staff review AI output at first; automation increases as accuracy is proven.
05
Improve
Evaluation and tuning continue as your data, products and policies change.
05 — Work
AI we have shipped
Own product
AI Counsellor
A WhatsApp AI agent that qualifies leads and books appointments for study-abroad consultancies, around the clock, in the language the student types in.
Own product
JewelShoot
AI jewellery photography: one product photo becomes catalogue-ready on-model shots and reels in under a minute.
jewelshoot.comClient work
MindLight AI
An AI-powered SaaS platform delivering insights and automation for productivity teams.
Client work
Ash Inc
An AI job-hunting dashboard with intelligent matching, built on Supabase.
Locations
AI solutions & development near you
We deliver remotely from Jaipur. Each location guide covers local industries, tax and data rules, and how working hours line up.
MumbaiDelhiBengaluruNew York CityLos Angeles, CAChicago, ILLondonManchesterBirmingham, UKBerlinParisAmsterdamDubaiRiyadhAbu DhabiLagosNairobiJohannesburgSingaporeKuala LumpurJakartaSydneyMelbourneBrisbaneMexico CitySão PauloBogotá
Country guides
FAQ
AI solutions & development: common questions
What do AI development services include?
Finding the right use case, preparing and connecting your data, choosing models, building the application (assistant, document pipeline, forecast or product feature), integrating it with your systems, testing it against real examples, and monitoring quality and cost after launch.
How much does AI development cost?
It depends on scope: a focused proof of value on one workflow is far smaller than a production system integrated with several tools. Model usage is a separate running cost that depends on volume; we estimate it up front and design to keep it low, for example with caching and smaller models where they are good enough. We quote a fixed scope after discovery.
How long does an AI project take?
A focused proof of value on your own data comes first and is short. Production builds then follow in two-week increments; how long they take depends mostly on how many systems the AI has to connect to and how clean the data is.
Will the AI make things up?
Only if it is built to guess. We ground answers in your own documents and data, restrict each system to a defined scope, hand off to a person the moment a question falls outside it, and log every output so you can audit it.
Is our data used to train AI models?
Not by us. With commercial model APIs we use business terms and settings under which the providers state they do not train on your data, and for sensitive cases we can run open-weight models inside your own cloud. Exactly what leaves your environment is agreed in writing before the build.
Do we need a lot of data to start?
Usually not. Knowledge assistants work from the documents you already have, and document AI needs a few dozen real examples to test against. Forecasting is different: it needs transaction history long enough to show your seasonality.
Can AI work in Hindi, Arabic, Spanish or other languages?
Yes. Current language models handle most major languages, including mixed-language messages such as Hinglish. We test in every language you need before launch, because quality varies by language and by model.
How do I choose an AI development company?
Ask to see AI systems they run in production, not demos; ask how they measure accuracy and what happens when the AI is unsure; check who owns the code and the prompts; and make sure the people on the sales call are the people who will build it. With us, you talk to the engineers writing the code.
Contact
Let's build it.
Tell us about the process you want fixed. We reply within one working day.
- Emailflip.retail1@gmail.com
- Phone / WhatsApp+91 92569 97690
- StudioB-2, B203 Brij Villa,
Rajendra Marg, Bapu Nagar,
Jaipur, Rajasthan 302015, India