Document & Knowledge Intelligence
Your best documentation is trapped
in your worst search tool.
AI that reads your SOPs, contracts, policies, and internal docs — and answers with citations. Permission-aware. Deployed in your VPC or on-prem. Zero hallucination tolerance for compliance teams.
The knowledge is there. Nobody can find it.
Your documentation is good. Your search isn’t. So the knowledge sits unused — and people guess, or worse, paste confidential docs into public chatbots.
We build permission-aware RAG assistants that read your documents and answer with citations, deployed inside your perimeter. Grounded answers only — if it can’t cite a source, it won’t answer.
Sound familiar?
- New hires take 3–6 months to ramp because no one can find anything
- Contract teams spend hours locating clauses across thousands of agreements
- Support teams answer the same questions with conflicting answers
- Employees paste confidential docs into ChatGPT because intranet search is unusable
What we build
Grounded, permission-aware assistants for employees, support, contracts, compliance, and sales.
Employee knowledge assistants
Ask anything about policies, SOPs, benefits, IT, HR, compliance — get a cited answer in seconds. Deployed in Slack, Teams, your intranet, or a custom chat UI.
Customer support knowledge bots
Grounded on your help center, internal playbooks, and product docs. Deployable as a chatbot, WhatsApp bot, or agent-facing co-pilot.
Contract intelligence
Search, summarize, and extract clauses across thousands of agreements. Compare contracts, flag missing terms, and auto-draft from templates.
SOP & compliance assistants
For BFSI, pharma, and healthcare — answers tied to the current version of a policy, with clause-level citations and audit trail.
Sales enablement assistants
Grounded on battle cards, win/loss notes, and case studies. Instant answers during discovery calls.
RFP & proposal assistants
Pulls from your response library, past proposals, and product docs. Drafts responses with citations.
How we build it
- Grounded answers only — every answer links to source doc + page; if it can’t cite, it won’t answer
- Permission-aware — inherits source ACLs (SharePoint, Drive, Confluence); no leakage across roles
- Your cloud, your control — VPC/on-prem with open models; no data leaves your perimeter
- Real-time sync — when a document updates, the index updates; no stale answers
- Eval-first — citation precision and answer accuracy measured against a domain test set, weekly
- Multi-modal — PDFs with tables/images, scans, handwriting, audio transcripts
How it works
Week 0 — Knowledge audit
What you have, where it lives, access patterns, and the accuracy bar.
Weeks 1–3 — Build
Ingestion pipeline, embeddings, retrieval, LLM orchestration, permissions, and UI.
Week 4 — Deploy
Internal pilot and eval tuning.
Weeks 5–6 — Scale
Full rollout, monitoring, and feedback loop.
Why MeghRoop
Built in your cloud, not ours
VPC/on-prem deployment with open models. No data leaves your perimeter.
Accuracy-measured
Every RAG build has an eval harness with citation precision + answer accuracy measured weekly.
Ships as a real assistant
WhatsApp, Slack, Teams, web, voice — not just a search box.
Domain-specific
Pharma SOPs, BFSI compliance, legal contracts — not generic enterprise search.
India pricing, US quality
4–6 week pilots vs. 6-month enterprise rollouts.
How we compare
Domain-tuned RAG vs raw LLM chat vs enterprise search.
| MeghRoop | Raw LLM (ChatGPT) | Enterprise search | |
|---|---|---|---|
| Answers with citations | Yes — sourced to doc + page | No — hallucinated summaries | No — returns links |
| Handles proprietary docs | Yes — PDF, Word, Confluence, SharePoint, Notion | Only if uploaded each session | Depends on indexing |
| Hallucination control | Strict — only from your corpus | Medium — may go off-source | N/A — keyword match |
| Private deployment | Yes — your cloud or on-prem | No — data leaves your env | Yes (on-prem SharePoint) |
| Time to production | 4–6 weeks | N/A | 3–6+ months |
Outcomes you can expect
Connects to everything you already store
Doc stores — SharePoint, Google Drive, Confluence, Notion, Dropbox, OneDrive, Box
Collaboration — Slack, Microsoft Teams, internal wikis, email archives
Systems — Zendesk, Salesforce attachments, databases, custom document stores
Repositories — PDF libraries, contract repositories, scanned archives
Engagements
Start with a scoped pilot, scale to production.
Pilot
$15K–$40K
One use case, one data source, 4–6 weeks.
Production build
$40K–$150K
Multi-source, multi-channel deployment.
Managed retainer
$2K–$10K/mo
Tuning, evals, re-indexing, and new sources.
Things worth actually answering.
Turn your documents into instant, cited answers.
Start with a knowledge audit. We’ll map what you have, set the accuracy bar, and stand up a pilot in 4–6 weeks.