400 papers in. The questions you couldn’t ask out.
ExComS Knowledge Agent turns a research corpus into a working partner. Upload 400+ papers; the Agent answers questions across the literature, surfaces gaps and grey areas, identifies hidden gems — questions raised but never followed up — and helps you build the cross-paper reference web that a thesis needs.
It’s the research assistant that doesn’t get tired at paper 80, doesn’t lose its place at paper 200, and doesn’t forget what it read last Tuesday.
Three ways researchers use it
Upload your reading list. Ask the Agent the questions a literature review needs to answer — who agrees with whom, which findings replicate, which methodologies dominate, where the gaps live. Get answers grounded in the corpus, not the public web.
Ask “what questions does this body of work raise but not answer?” The Agent surfaces threads the field hasn’t pulled — your thesis-shaped opportunities. The same query against PubMed or Google Scholar returns nothing useful; against your curated corpus it returns the next research question.
Drafting a chapter? The Agent identifies which papers cite which, surfaces the lineage of an argument, and finds the citations you missed. Stop hunting through PDFs by hand.
Three-step setup
Drag-and-drop your reading list. PDFs, scanned papers, anything text-extractable.
Every paper, every section, every citation. Held in your private knowledge base.
Natural-language questions; answers grounded in your corpus with paper-level evidence.
Weeks to hours.
A literature review that takes weeks of researcher time runs in hours. Cross-paper reference mapping that takes days runs in minutes.
Days of reading and skimming becomes seconds. Citations always returned with the answer.
Months of cross-reading becomes hours. The Agent surfaces threads the field hasn’t pulled.
Hours per chapter, by hand, becomes minutes. Lineage of an argument visible across the corpus.
Manual research vs. AI Knowledge Agent
| Activity | Manual / typical tool | With Knowledge Agent |
|---|---|---|
| Search 400+ papers for a specific argument | Days of reading + skimming | Seconds |
| Identify gaps in the literature | Months of cross-reading | Hours |
| Map citation lineage across a chapter | Hours per chapter, by hand | Minutes |
| Find hidden questions / “research gems” | Often missed entirely | Surfaced systematically |
| Onboarding a new RA to your corpus | Weeks | One-time corpus upload |
| Re-checking facts at thesis defence | Re-reading every paper | Targeted queries with citations |
3 weeks
Hours
Why this beats NotebookLM (and similar)
- Researcher-built — gap analysis, hidden-gem surfacing, cross-paper citation mapping, thesis-drafting hooks. Not a generic Q&A tool.
- Citations as a first-class feature — every answer pinpoints the paper, page, and passage. Audit-ready.
- Corpus stays private — not pooled with anyone else’s reading list, not used to train public models.
- UK data residency — Azure UK South, mandatory for university and NHS data handling.
- Institutional procurement-ready — DPA template, GDPR Article 28, sub-processor list public.
Citation-grounded, UK-hosted, private to your network.
Common questions.
How is this different from NotebookLM?
NotebookLM is a generic note-and-Q&A tool. Knowledge Agent is researcher-built — it does literature-review-shaped tasks (gap analysis, hidden-gem surfacing, citation lineage mapping, thesis drafting hooks) that NotebookLM doesn’t. We also offer UK data residency and an institutional procurement path.
How big a corpus can it handle?
400+ papers is a working assumption. Architecture scales beyond that as researchers’ needs grow — talk to us about heavier corpora.
Does it learn from my corpus to improve other users’ results?
No. Your corpus is private. Not pooled, not used to train public models, not visible to other users.
What about citations? Can I trust it?
Every answer pinpoints the paper, page, and passage it draws from. You always cross-check before you cite — but you don’t have to start from scratch.
Is there an institutional pilot path?
Yes. We’re talking with university research offices and NHS knowledge teams. Talk to us if you want to scope a pilot for your institution.
Is it on Microsoft Marketplace? G-Cloud?
MS Marketplace listing in progress. G-Cloud listing under consideration for the regulated-industry pursuit. Today: direct engagement.
Asset pack
Product deck, flyer, and 50-second explainer video.
Ready to read 400 papers in seconds?
We’re working with UK university research offices and NHS knowledge teams. Talk to us about scoping a pilot for your institution.
