Specialist literature monitoring
Narrow relevance criteria and inspectable inclusion decisions.
- For
- R&D teams tracking one applied research topic
- Solves
- Broad alerts overwhelm researchers with irrelevant papers.
- Delivers
- Reviewed literature monitoring digest
- Built in
- about 2 weeks of creation time, MVP in 2 days
- Investment
- $5,500 for the MVP, $17,000 for the full product
- Run it
- Inside your business, or as part of your offer to clients
What it does
For r&D teams tracking one applied research topic, turn licensed or openly accessible papers and topic criteria into reviewed literature monitoring digest.
- Screen topical relevance.
- Identify duplicate versions.
- Extract study context.
- Summarize reported findings.
- Preserve limitations.
- Publish cited digests.
What goes in, what comes out
- Licensed or openly accessible papers
- Topic criteria
AI drafts, people review. Watchlist, change detection and briefing subscription.
- Reviewed literature monitoring digest
How it works
The workflow
- InStart with
Licensed or openly accessible papers and topic criteria
- 1
Agree a narrow watchlist
- 2
Confirm lawful source access
- 3
Collect dated snapshots
- 4
Detect candidate changes
- 5
Review relevance and accuracy
- 6
Deliver a concise digest
- 7
Refine the watchlist from buyer feedback
- OutFinish with
Reviewed literature monitoring digest
AI does the heavy lifting, people stay in charge
Classify source material, group related developments and summarize verified changes. Use deterministic snapshot comparison for factual changes where possible. Distinguish observed publication content from analyst interpretation and uncertain implications.
What your team sees
Key screens: Topic feed, paper evidence, digest review. Use a watchlist with source health and last-checked dates, a chronological change feed, and a reviewable briefing editor. Display original evidence beside each alert. Let users mute irrelevant topics and record whether a change led to action. In this product, the first view is topic feed, followed by paper evidence and digest review.
Accounts and administration
Watchlist ownership, source health, dated evidence, deduplication, topic filters, editorial review, delivery preferences and alert feedback.
Integrations and data access
Authorized datasets, papers, protocols, code and research records. Permitted feeds, published document sources, email digests and internal briefing channels. Verify collection rights and source reliability before selling coverage commitments. These are candidate integration categories, not verified supported connectors.
How we build it
We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.
- 1
Scoping call
Day 1Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.
- 2
MVP
2 daysOne buyer segment, one recurring use case; first modules: screen topical relevance; identify duplicate versions. Manual review in the loop. Built by our AI software factory.
- 3
Paid pilot
3 daysAccounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.
- 4
Full product
6 daysRemaining modules: summarize reported findings; preserve limitations; publish cited digests. Self-serve onboarding, billing, monitoring and the wider integration set.
- 5
Run and improve
MonthlyWe host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.
Why we start with an MVP
An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.
- Pick the riskiest assumption. Here: will R&D teams tracking one applied research topic use it to solve "broad alerts overwhelm researchers with irrelevant papers"?
- Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
- Run a paid pilot. Deliver several scheduled digests for a small watchlist.
- Measure, then decide. Track relevant inclusions and missed key papers. Then expand, change course or stop, with evidence instead of opinions.
MVP scope for this solution. Begin with r&D teams tracking one applied research topic and one recurring use case. Build the first two modules: screen topical relevance; identify duplicate versions. Provide operator assistance for the third module: extract study context. Deliver reviewed literature monitoring digest through a manual review queue. Perform other necessary full-scope functions manually during the pilot. Include all applicable access, accuracy and professional-review controls from the start.
After the MVP. After paid pilots establish value, automate the remaining modules: summarize reported findings; preserve limitations; publish cited digests. Add one validated source integration, reusable customer configuration and recurring delivery. Expand to additional teams, document formats or languages only after testing the new scope.
What the build depends on. Reliable permitted source access, change history, publication dates, deduplication and editorial QA. Coverage limits and inaccessible sources must be visible.
Investment
A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.
- Phase 1
MVP
One buyer segment, one recurring use case; first modules: screen topical relevance; identify duplicate versions. Manual review in the loop.
- Phase 2
Paid pilot
Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.
- Phase 3
Full product
Remaining modules: summarize reported findings; preserve limitations; publish cited digests. Self-serve onboarding, billing, monitoring and the wider integration set.
Indicative total, MVP to full product$17,000about 2 weeks of creation time · start with the MVP from $5,500
Running costs per month
A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.
| Stage | Hosting and infrastructure | AI usage | Total per month |
|---|---|---|---|
| MVP and paid pilotabout 3 customers | $30–$60 | $50–$100 | $80–$160 |
| Full productabout 50 customers | $110–$210 | $350–$700 | $460–$910 |
Run it or resell it
For your own team
R&D teams tracking one applied research topic run it inside the business: licensed or openly accessible papers and topic criteria in, reviewed literature monitoring digest out, reviewed by your people.
As part of your offer
Agencies, consultancies and software companies can offer it to their own clients under their brand. We build and maintain it; you sell and deliver it.
Your brand, or this one
Run it under your own brand, or start from this concept style.
- primary
#91274c - accent
#54c995 - surface
#f1e4e9 - ink
#22201e
- Headings
- Playfair Display
- Text
- Source Sans 3
- Voice
- Rigorous, transparent, cited
Selling it to your own clients: the go-to-market playbook
Pricing to test
Test USD 100-500 monthly for a narrow shared briefing, or USD 750-2,500 monthly for bespoke analyst coverage. Licensed source access and unusual collection requirements are extra. Prices require validation.
Message to test
Specialist literature monitoring for r&D teams tracking one applied research topic. Narrow relevance criteria and inspectable inclusion decisions. Demonstrate the claim through a source-linked weekly literature digest.
Where to find buyers
Specialist research societies
Lead magnet
A source-linked weekly literature digest
The first 30 days
- Week 1: interview five prospective buyers in this segment: r&D teams tracking one applied research topic. Ask to see a recent example of the problem and their current process.
- Week 2: prepare this demonstration using authorized or synthetic material: a source-linked weekly literature digest.
- Week 3: present it through specialist research societies and seek one narrowly scoped paid pilot.
- Week 4: review relevant inclusions, missed key papers, total delivery effort and a concrete renewal decision before increasing scope.
Paid pilot
Deliver several scheduled digests for a small watchlist. Have the buyer label useful and irrelevant items, independently check important missed developments and assess whether the briefing changes a decision. For this solution, use licensed or openly accessible papers and topic criteria and evaluate reviewed literature monitoring digest. Agree success thresholds with the buyer before starting; collect a baseline for relevant inclusions, missed key papers. A positive signal is payment and repeat use with acceptable quality and delivery cost, not a favorable demo reaction alone.
Success metrics
Relevant inclusions, missed key papers
Retention and expansion
Tune relevance from buyer feedback, preserve historical changes and offer deeper analyst review for selected topics. Add sources only when they improve useful coverage.
Why clients would pick it
A curated source network, historical change archive and buyer-specific relevance judgments within a narrow topic. For this solution, build around narrow relevance criteria and inspectable inclusion decisions. This advantage requires execution and accumulated customer trust; the base model alone is not a defensible asset.
Alternatives and positioning
Newsletters, search alerts, analysts and general media or website monitoring tools. Differentiate on this specific proposed advantage: narrow relevance criteria and inspectable inclusion decisions. Test it against the buyer's current method on the same task. Competitor coverage and uniqueness have not been established.
Main delivery costs
Source licensing, collection reliability, change processing, analyst verification, missed-signal review and digest production.
Safeguards
Preserve original data, methods, citations and research limitations. Use researcher review and document every substantive transformation. Validate source access and reviewer availability during the pilot. Maintain customer-level access, data deletion controls and a record of final approvals.