Why Businesses Choose Us
Quick answers
- Builds: AI assistants, RAG search, AI agents, document automation, NL interfaces - Models: Claude, GPT, Gemini, Llama and other open-source models - Stack: Python, TypeScript, vector databases, your cloud (AWS, Azure, GCP) - Quality: evaluation sets, guardrails, human-in-the-loop - Engagement: fixed-scope prototype, then production build or dedicated team
What We Automate
⚡
AI assistants on your data
Answers grounded in your documents. - Retrieval-augmented generation (RAG) - Source citations - Access controls by role
💬
AI agents & workflow automation
Multi-step tasks done automatically. - Tool-using agents - Approval steps - Integration with CRMs and ERPs
📊
Document intelligence
Read, extract and generate documents. - Invoice and form extraction - Contract and report summaries - Automated document generation
🛠️
Natural-language interfaces
Let users type what they mean. - Plain-English data entry - Chat-to-query dashboards - Voice and WhatsApp interfaces
✍️
AI inside your SaaS product
Ship AI features your customers will use.
Copilots and smart suggestions
Summaries and auto-tagging
Usage-based cost controls
🔗
Evaluation & guardrails
Measure quality before you launch.
Test sets and accuracy scoring
Prompt injection safeguards
Monitoring and feedback loops
Industries We Serve
AI we have built into real products
Teams log work in plain English; the system structures it.
Receipts and certificates generated from one person record.
SEO and LLM visibility for an AI platform.
Areas We Cover
Have an AI idea but unsure it is feasible? We run a 1-week discovery sprint that ends in a clear build plan and cost estimate.
United States & Canada
SaaS companies adding AI to their product.
United Kingdom & Europe
Enterprises automating operations, GDPR-aware delivery.
UAE & Middle East
Government-adjacent and enterprise automation.
Australia
GLOBAL
Service businesses and startups.
India (team base)
AI engineering team in Delhi NCR.
Why Fameweb
Why companies build AI with Fameweb
1
Product first, model second
We design the workflow before choosing the model.
2
Measured accuracy
Every feature ships with an evaluation set, not a gut feeling.
3
Your cloud, your data
We deploy in your account so data stays under your control.
4
Full-stack team
UX, front end, back end and AI engineering in one team.
Hire From Us
Hourly
MIN 10 HRS
Pay only for the hours you actually use, nothing more.
— Small fixes and one-off tasks
— Logged hours you can audit
— No monthly commitment
Part-time
40–80 HRS / MO
A fixed block of hours every month, same person throughout.
Full-time
160 HRS / MO
One person working only on your business, full month.
— Like an in-house hire, without hiring
— Your tools, your process
— Backup cover when they are on leave
You brief them directly.
We handle the contract, the leave cover, and a replacement if someone is not the right fit.
FAQ
How much does it cost to build an AI app?
A focused prototype is a fixed-scope project, and production builds are scoped after the prototype proves value. Model usage costs are estimated upfront and monitored.
Which AI model should we use?
It depends on accuracy, speed, cost and data requirements. We test leading models such as Claude, GPT and Gemini, plus open-source options, against your real tasks before choosing.
Is our data safe?
Yes. We work under NDA, deploy in your cloud account, use providers' business APIs that do not train on your data, and apply role-based access controls.
How long does it take to build an AI prototype?
A working prototype on your real data typically takes 3 to 6 weeks.
