Ingestion & parsing
Tables and contracts parsed with structure intact.
DISCOVERY SPRINT · 2 WEEKS
Prove a grounded LLM can answer your hardest questions — in two weeks, before you commit to a build.
Fixed price. Scoped design and ROI math are yours either way. We'll also tell you if RAG is the wrong tool for what you need.
01Fixed price, agreed up front
02Two-week scoped Sprint
03Keep the design + ROI math either way
Book a Discovery Sprint →
The first call is free · 45 minutes · no obligation
02 · Dogfooding
Software a vendor hopes works, versus software a vendor depends on.
The pitch you're used to
Staged for the room.
- Built to demo, not to survive daily use
- No internal team betting its own output on it
- Failure modes surface after you've signed
What Banao runs internally
Staged for our own 300-person team, first.
- InterviewGod hires for us, every role
- Vikaas runs our own outreach pipeline
- Vidya upskills our own engineers before clients
ASSET PENDING — internal usage dashboard snapshot
03 · WHAT WE BUILD
Ten stages. Every one scored, none skipped.
This is what a Discovery Sprint actually tests on your documents — not a demo of the last one.
Chunking
Cuts drawn around meaning, checked against your tables.
Embedding & index
Built on your domain vocabulary.
Hybrid retrieval
Keyword and vector search, scored against each other.
Re-ranking
A second pass for real relevance, not top-k luck.
Grounding
Answers cite the passage they came from.
Abstention
No evidence, no answer — by design.
Guardrails
PII and policy checks before output ships.
Evaluation harness
Scored against your hardest questions, not ours.
Freshness monitoring
Index drift watched after go-live.
04 · WHERE PILOTS BREAK
Confident, wrong answers all trace back to one of four gaps.
01
Retrieval was never measured
No precision/recall baseline existed before launch — so nobody could tell degradation from day one.
02
Chunking cut answers in half
Fixed-size splitting sliced tables and steps mid-sentence.
03
No path to "I don't know"
Low-confidence matches still returned confident, fabricated answers.
04
The index went stale
Source documents changed weekly; the vector index re-synced quarterly, if at all — correct on day one, wrong by day thirty.
05 · HOW WE ACTUALLY BUILD A RAG SYSTEM
This is the internal bar we hold ourselves to.
Every answer our own 300-person team pulls from our internal RAG assistant goes through the same four checkpoints we build for clients. We don't skip a step for our own system, and we don't skip one for yours.
- 01Structure-aware chunking — tables and clauses survive the split.
- 02Retrieval, measured — hybrid search plus re-rank, scored against a labeled question set.
- 03Grounded generation — answers only from what retrieval returns, with abstention built in.
- 04Citation and refresh — every answer sourced, every index re-synced on schedule.
06 · RAG, Fine-Tuning, or Both
Three options. Only one fits what you actually need.
Most budgets get spent before this question gets answered. Here's how we decide — by what breaks if you guess wrong, not by what's trending.
01
RAG
When your facts change weeklyPricing, inventory, policy, ticket history — anything that goes stale. The model reads from a live index at answer time, so the system stays current without retraining.
02
Fine-Tuning
When the facts don't move, the behavior doesHouse tone, output format, a domain vocabulary your team already speaks fluently. Fine-tuning bakes in how to answer — it doesn't help the model know more.
03
Both
When you need current facts said your wayRAG supplies what's true today; fine-tuning supplies how your company says it. Most production systems we've shipped end up here — not because it's safer, but because both jobs were real.
Fourth option: neither
If the answer already lives in a fixed rulebook — a decision table, a policy doc with three branches — a smaller rules-based system beats either, at a fraction of the cost. We'll tell you if that's your case before we scope anything larger.
07 · Receipts
What "unproven pilot" looks like, next to what we actually run.
Typical first attempt
–Retrieval never measured against real questions
–No abstention path — the model guesses instead of saying "I don't know"
–Index goes stale within weeks of launch
–Demoed once, then shelved
Running today
✓InterviewGod — internal hiring, cited answers daily··%
✓Vikaas — internal outreach, retrieval eval'd continuously··×
✓Majra (UAE) — client system, live in production··min
✓Same stack, 300-person internal team depends on it
Asset Pending — Dashboard Screenshot
08 · WHERE WE DELIVER
Five offices. Three regions. Zero handoff to a subcontractor.
We don't route your engagement through a partner network. Every one of our 30+ production clients is served directly, from one of these desks.
01Bengaluru, IndiaPrimary engineering base
02ChandigarhIndia
03DubaiUAE
04CambridgeUK
05CaliforniaUS
09 · The Honest Version
We turn away the wrong build. Here's the map.
Filter
Disqualifying early is cheaper than a failed second pilot
Four checks decide whether a Discovery Sprint is the right next step for you — before either of us spends two weeks on it.
01
Demo-only ask
Wants a convincing screen share, not a retrieval score on real documents.
02
Undigitized source
Scanned images, broken tables, no text layer to retrieve from.
03
No abstention allowed
Needs the system to always answer, even when it should say "I don't know."
04
Same-day deadline
Timeline measured in hours — not the two weeks a Sprint takes.
10 · How We Start
Committing budget to an unproven system, twice, is the actual risk.
A full build, no Sprint
–You commit to scope before retrieval is tested against your real documents.
–Failure surfaces months in, after budget is spent.
–No documented answer if the tool turns out to be wrong for the problem.
The Banao Discovery Sprint
+Retrieval is scored against your hardest questions in two weeks, fixed price.
+Scoped design and ROI math are yours whether or not you proceed.
+If RAG is the wrong tool, we tell you before you spend the budget on a build.
11 · FAQ
Questions that come up before a contract does
Answered plainly, in the order they come up when a team has been burned by a pilot once already.
How is this different from a chatbot demo?
Every answer our own 300-person team gets from our internal RAG assistant carries a citation. We run the same retrieval-and-eval stack on our own operation, every working day, before it reaches a client.
What if RAG isn't the right fit for what we need?
The Discovery Sprint tests retrieval feasibility on your real documents and hardest questions. If the answer is no, we say so before you commit to a build.
What does the Sprint cost, and what do we keep either way?
Fixed price, two weeks. The scoped design and ROI math are yours whether or not you continue with us.
Do we own the system once it's built?
Yes. You own the system, with no lock-in — that's one of the four pillars we hold every engagement to.
How fast can this actually ship?
Weeks, not quarters. It's shipped as production AI, not slideware.
What happens to our tables and PDFs?
Retrieval quality is measured, not assumed — chunking is built around your document structure, not a naive default that cuts tables in half.
Who has actually done this before?
30+ clients since 2016, including Swiggy, Myntra, PhonePe, Times Internet, Indian Oil, HCL, CP Plus, RAK Ceramics, FootLocker and Majra.
Can you work with our timezone?
We operate out of Bengaluru, Chandigarh, Dubai, Cambridge (UK) and California — coverage across US, UAE and India hours.
12 · Related links
More on how we build, and who we've built it for.
13 · GET STARTED
Find out what actually broke — before you spend budget on a second attempt.
Bring the questions your team currently answers by hand. In 45 minutes we'll tell you whether retrieval can hold on your documents, or whether RAG is the wrong tool for what you need.
Book a Discovery Sprint →
Fixed price · two weeks · yours either way
01
We measure retrieval on your real documents
02
We score it against your hardest questions
03
You leave with a diagnosis, not a demo