Government · Public records search
The file exists. Finding it takes three departments and a morning.
Banao builds an AI search layer over your digitized records — land registers, case files, RTI responses, licence archives — so a clerk types a plain-language query and the right document surfaces in seconds, not after a walk to the records room.
The system sits on top of your existing document store, on-premise or in a sovereign cloud, with access controls that mirror your department's rules exactly.
What the search deployment includes
A search layer is only as useful as the index beneath it. We build both — and we make the data-cleaning work the first measurable deliverable.
Plain-language query across structured and unstructured records
Officers type how they think, not how the record was filed. The system retrieves across scanned PDFs, typed registers, and database entries — regardless of how each department labelled its files.
Digitization and OCR as the opening deliverable
Where records are still on paper, Banao runs OCR and handwriting extraction first. The search index is built on a clean, searchable corpus — not a scan pile that stops at keyword match.
Access control baked into every result
A citizen-facing portal sees different results than an officer's desk search. Permissions mirror your department hierarchy and are enforced at the index layer, not by frontend filtering.
Multilingual queries and document handling
Records filed in Hindi, Urdu, Kannada, or Arabic return correctly against queries in any of those languages. The model does not require the user to know the language the record was filed in.
Audit trail on every retrieval
Each document access is logged — who retrieved what, when, and under which authorisation. RTI compliance and internal audit requirements are met without a separate tracking system.
Relevance tuning to government record types
Land survey numbers, case IDs, scheme codes, and government file notations are treated as structured entities, not free text. Relevance ranking is tuned so the right file appears first, not the most-mentioned one.
We operate a 300-person company on the same AI infrastructure
Banao's own 300-person engineering operation runs on the AI systems we build for clients. InterviewGod handles our hiring intake. Vikaas runs our demand-generation pipeline from lead to brief. We are not describing AI from the outside.
When a government department's search system has to find the right file on the first query, we treat that the same way we treat our own internal tools — it has to work every time, or we fix it before it goes near a public counter.
- InterviewGodScreens Banao's own engineering candidates — our hiring desk, every week.
- VikaasRuns Banao's own demand-generation pipeline end to end.
When AI search is the wrong starting point
We tell departments when the sequencing is wrong — before a budget is committed:
- No digital corpus yet: if records are fully on paper with no prior digitization, the first project is digitization. Search needs a database; we build that first and scope the search phase separately.
- Too few queries to justify a build: a records room that handles a dozen retrievals a week rarely repays an AI search build. A structured folder system and a trained clerk usually beats it at that volume.
- Overlapping classification schemes: when ten departments have filed the same category of record ten different ways, a search layer built before data cleaning will produce noisy results. We do the cleaning work first.
How we start — fixed-price, low risk
We audit your records before we quote a search system. Two weeks to know what you have and what it will cost.
- AI Discovery Sprint2 weeks · fixed price
We assess your existing records corpus — volume, format, language mix, classification quality — and hand back a search feasibility report with a retrieval-accuracy estimate and a cost/benefit figure. Yours to keep. Proceed, and the Sprint fee is credited against the build.
- Build
OCR and digitization pipeline first, then the search index. Access-control mapping, multilingual model tuning, and integration with your existing records management system are part of the deliverable.
- Production & handover
Deployment with staff training, a retrieval audit trail, and a documented handover. We run a support window and leave your team able to manage the system without ongoing dependency on us.
Frequently asked questions
Our records are still largely on paper. Can we still build a search system?
Yes — digitization is step one, and we do both. Banao runs OCR and handwriting extraction as the opening deliverable, so the search index is built on a clean corpus. The digitization phase itself produces the first measurable result: a searchable database where there was none.
Can the system handle records in multiple Indian languages?
Yes. The search layer handles queries and documents in Hindi, Urdu, Kannada, Tamil, Arabic, and English, and can retrieve a record filed in one language when the query is typed in another. The language mix in your corpus is assessed during the Discovery Sprint.
How do we prevent officers from accessing files above their clearance?
Access controls are enforced at the index layer, not the frontend. Each officer's query runs against only the documents their role permits. The permission model mirrors your department hierarchy and is a built deliverable, not an afterthought.
Does this work if different departments use different filing systems?
It is designed for exactly that. The model normalises across classification schemes and treats department-specific file codes, survey numbers, and case IDs as structured entities. Where classification is particularly inconsistent, a data-cleaning step precedes the index build.
How does this satisfy RTI and audit requirements?
Every document retrieval is logged with the officer's identity, timestamp, and authorisation basis. The audit trail is stronger than a manual records-room sign-out sheet and is available for RTI and internal audit without a separate reporting tool.
Find out how fast your records room could answer a query
Bring a description of your current retrieval bottleneck — paper volume, filing inconsistency, or multilingual backlog. In 45 minutes we'll map what a search layer would take and what it would return.
Book a 45-min scoping call