Research document search cover

Research document search

Project-aware permissions and document provenance for internal research.

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For
Laboratory managers with growing internal archives
Solves
Useful findings and protocols are hard to retrieve.
Delivers
Source-linked research search results
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
01

What it does

For laboratory managers with growing internal archives, turn authorized research documents and project permissions into source-linked research search results.

  1. Index permitted documents.
  2. Filter projects.
  3. Retrieve exact passages.
  4. Preserve version context.
  5. Flag conflicting findings.
  6. Export citations.

What goes in, what comes out

What the customer puts in
  • Authorized research documents
  • Project permissions

AI drafts, people review. Source-linked assistant and administrator console.

What the customer gets
  • Source-linked research search results
02

How it works

The workflow

  1. In
    Start with

    Authorized research documents and project permissions

  2. 1

    Add an approved collection

  3. 2

    Assign source owners and access rules

  4. 3

    Test representative questions

  5. 4

    Let users ask questions

  6. 5

    Retrieve supporting passages

  7. 6

    Answer or request clarification

  8. 7

    Hand off unresolved cases with their context

  9. Out
    Finish with

    Source-linked research search results

AI does the heavy lifting, people stay in charge

Retrieve permitted passages and generate answers constrained to those sources. Use structured rules for transactional facts. Detect missing context and refuse to invent unsupported details. Store reviewer corrections for evaluation and controlled knowledge updates.

What your team sees

Key screens: Research search, cited passage, collection ownership. Give end users a simple search or conversation surface with short answers and expandable citations. Administrators get source status, unanswered questions and handoff queues. Show the source date beside relevant answers. Keep conversation context available to the staff member receiving an escalation. In this product, the first view is research search, followed by cited passage and collection ownership.

Accounts and administration

Source ownership, document permissions, freshness checks, conversation history, human handoff, feedback, test questions, usage limits and access logs.

Integrations and data access

Authorized datasets, papers, protocols, code and research records. Approved knowledge repositories, websites, service desks and staff messaging systems. Validate access inheritance and use read-only ingestion for the initial deployment. These are candidate integration categories, not verified supported connectors.

03

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. 1

    Scoping call

    Day 1

    Thirty 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. 2

    MVP

    2 days

    One buyer segment, one recurring use case; first modules: index permitted documents; filter projects. Manual review in the loop. Built by our AI software factory.

  3. 3

    Paid pilot

    3 days

    Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

  4. 4

    Full product

    6 days

    Remaining modules: preserve version context; flag conflicting findings; export citations. Self-serve onboarding, billing, monitoring and the wider integration set.

  5. 5

    Run and improve

    Monthly

    We 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.

  1. Pick the riskiest assumption. Here: will laboratory managers with growing internal archives use it to solve "useful findings and protocols are hard to retrieve"?
  2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
  3. Run a paid pilot. Restrict the assistant to one collection and test answered, ambiguous and unanswerable questions.
  4. Measure, then decide. Track relevant retrieval and permission correctness. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. Begin with laboratory managers with growing internal archives and one recurring use case. Build the first two modules: index permitted documents; filter projects. Provide operator assistance for the third module: retrieve exact passages. Deliver source-linked research search results 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: preserve version context; flag conflicting findings; export citations. 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. Permission-filtered retrieval, document versioning, a question evaluation set, staff handoff and a source update process. Reliability depends on source quality and scope.

04

Investment

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

  1. Phase 1

    MVP

    One buyer segment, one recurring use case; first modules: index permitted documents; filter projects. Manual review in the loop.

    $5,500 · about 2 days of creation time

  2. Phase 2

    Paid pilot

    Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

    $5,000 · about 3 days of creation time

  3. Phase 3

    Full product

    Remaining modules: preserve version context; flag conflicting findings; export citations. Self-serve onboarding, billing, monitoring and the wider integration set.

    $6,500 · about 6 days of creation time

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.

StageHosting and infrastructureAI usageTotal per month
MVP and paid pilotabout 3 customers$30–$60$60–$120$90–$180
Full productabout 50 customers$110–$210$530–$1,050$640–$1,260
05

Run it or resell it

Internally

For your own team

Laboratory managers with growing internal archives run it inside the business: authorized research documents and project permissions in, source-linked research search results out, reviewed by your people.

For your clients

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#912756
  • accent#54c9a2
  • surface#f1e4ea
  • 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 500-2,000 setup plus USD 150-600 monthly for one defined source collection and usage allowance. Price multi-location deployments and specialist support separately. Validate willingness to pay; these are hypotheses.

Message to test

Research document search for laboratory managers with growing internal archives. Project-aware permissions and document provenance for internal research. Demonstrate the claim through a cited search demonstration on approved lab documents.

Where to find buyers

Research IT consultants

Lead magnet

A cited search demonstration on approved lab documents

The first 30 days

  1. Week 1: interview five prospective buyers in this segment: laboratory managers with growing internal archives. Ask to see a recent example of the problem and their current process.
  2. Week 2: prepare this demonstration using authorized or synthetic material: a cited search demonstration on approved lab documents.
  3. Week 3: present it through research IT consultants and seek one narrowly scoped paid pilot.
  4. Week 4: review relevant retrieval, permission correctness, total delivery effort and a concrete renewal decision before increasing scope.

Paid pilot

Restrict the assistant to one collection and test answered, ambiguous and unanswerable questions. Run supervised use before wider rollout. Measure correctness, escalation quality and staff effort. For this solution, use authorized research documents and project permissions and evaluate source-linked research search results. Agree success thresholds with the buyer before starting; collect a baseline for relevant retrieval, permission correctness. A positive signal is payment and repeat use with acceptable quality and delivery cost, not a favorable demo reaction alone.

Success metrics

Relevant retrieval, permission correctness

Retention and expansion

Review unanswered questions and source freshness monthly. Expand to another source collection or team only after the existing assistant meets its agreed accuracy and handoff criteria.

Why clients would pick it

A maintained domain knowledge collection, realistic evaluation questions, useful escalation paths and integrations in the customer’s daily work. For this solution, build around project-aware permissions and document provenance for internal research. This advantage requires execution and accumulated customer trust; the base model alone is not a defensible asset.

Alternatives and positioning

Manual search, static FAQs, general chat tools and support or intranet suites. Differentiate on this specific proposed advantage: project-aware permissions and document provenance for internal research. Test it against the buyer's current method on the same task. Competitor coverage and uniqueness have not been established.

Main delivery costs

Document ingestion, retrieval and generation, source maintenance, support, evaluation and staff time handling unresolved cases.

06

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.

Get this solution built

Built for you by our AI software factory, MVP in about 2 days. Tell us about your business and how you want to run it: inside your company, or as part of what you offer your clients. We reply within one working day.

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