Evidence-backed legal document review workspace

For

In-house counsel, contract managers and small legal teams reviewing agreements without full outside-counsel support

Solves

Legal documents are long and complex, so reviewers miss risky terms, repeat manual reading and cannot show where a conclusion came from.

Delivers

Reviewed risk report linked to clause text

Built in

about 6 weeks of creation time, MVP in 7 days

Investment

$13,000 for the MVP, $44,000 for the full product

Run it

Inside your business, or as part of your offer to clients

Reduce manual reading while keeping every finding traceable to the clause it came from.

1. Upload legal documents for analysis.
2. Convert complex legal language into plain-language summaries.
3. Detect potential risks and problematic terms.
4. Extract and highlight key clauses and terms.
5. Answer user questions about specific document parts.
6. Generate guiding questions on important aspects.
7. Filter by specific contract elements or criteria.
8. Produce reports with findings and suggested actions.
9. Integrate with document management systems.
10. Show how clauses could cause issues in real scenarios.
11. Customize analysis to user priorities.
12. Compare contract versions to highlight changes.
13. Provide a searchable repository of contract information.
14. Handle sensitive legal information securely.
15. Support customizable analysis models.
16. Upload and manage review playbooks.
17. Keep a centralized repository for contract files.
18. Compare the reviewed result with the recorded baseline and value assumptions.
19. Capture corrections and named-owner approval before consequential use.
20. Export a versioned reviewed risk report linked to clause text with source references and unresolved questions.

Everything these tools do, in one app

• Document Upload Allows users to upload legal documents for analysis.Found in LegalCheckPro, My Pocket Lawyer, FairPact AI and 3 more
• Plain Language Summaries Converts complex legal language into clear, easy-to-understand summaries.Found in LegalCheckPro, Docu, My Pocket Lawyer and 2 more
• Risk Detection Identifies potential risks and problematic terms in legal documents.Found in LegalCheckPro, Docu, SpeedLegal and 3 more
• Clause Identification Extracts and highlights key clauses and terms within contracts.Found in SpeedLegal, AI Contract Analysis, review.legal and 1 more
• Question Answering Answers user questions about specific parts of the document.Found in My Pocket Lawyer, Legalese Decoder
• Guiding Questions Generates relevant questions to help users focus on important aspects.Found in My Pocket Lawyer, FairPact AI
• Customizable Filters Allows users to focus on specific contract elements or criteria.Found in SpeedLegal, review.legal
• Detailed Reporting Produces reports summarizing findings and suggested actions.Found in SpeedLegal, AI Contract Analysis
• Document Management Integration Integrates with popular document management systems.Found in SpeedLegal, AI Contract Analysis
• Scenario Generation Shows how specific clauses could cause issues in real situations.Found in FairPact AI
• Personalized Analysis Customizes the analysis based on user priorities.Found in FairPact AI
• Version Comparison Compares multiple contract versions to highlight changes.Found in AI Contract Analysis
• Searchable Database Provides a searchable repository for easy retrieval of contract information.Found in AI Contract Analysis, Legal Graph
• Secure Handling Ensures secure handling of sensitive legal information.Found in review.legal, Legal Graph
• Customizable AI Models Allows customization of AI models for tailored analysis.Found in LegalCheckPro, Legal Graph
• Customizable Playbooks Enables uploading and managing playbooks to align contract reviews with standards.Found in Legal Graph
• Centralized Repository Provides a centralized system for contract file management.Found in Legal Graph

What goes in, what comes out

The workflow

1. In
   Start with

   Uploaded contracts, review playbooks, user priorities and prior contract versions

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect uploaded contracts

4. 3

   Playbooks

5. 4

   User priorities and prior versions

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   Reviewed risk report linked to clause text

AI does the heavy lifting, people stay in charge

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One contract type and one governing jurisdiction per pilot; final legal interpretation and risk acceptance remain with qualified counsel. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Matter intake and playbook setup, Editable review workspace, Client report and delivery. Use a document list for matters, a large central clause view with highlighted text, and a right-hand panel for risks, questions and comments. Let users compare contract versions side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant clause. Make the task-specific outcome reviewed risk report linked to clause text visible beside its evidence, review state and value baseline.

Accounts and administration

Matter ownership, document versions, client comments, approval states, usage allowances, review limits, download history and a rights record for supplied material. Add organization access boundaries, named reviewers, usage caps, data retention controls, export logs and explicit approval for external actions.

Integrations and data access

Client-owned contract repositories, document management systems and permitted research sources. Cloud document storage, design-file import/export and reporting destinations. Start with file exchange and validate destination specifications before promising direct filing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.

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

   7 days

   One buyer segment, one recurring use case; first modules: upload legal documents for analysis; convert complex legal language into plain-language summaries. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   8 days

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

4. 4

   Full product

   3 weeks

   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 in-house counsel, contract managers and small legal teams reviewing agreements without full outside-counsel support use it to solve "legal documents are long and complex, so reviewers miss risky terms, repeat manual reading and cannot show where a conclusion came from"?
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. Agree quality and outcome thresholds before the pilot using this measure: Reviewed clauses per reviewer hour and material risks missed after sign-off.
4. Measure, then decide. Track reviewed clauses per reviewer hour and material risks missed after sign-off; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. Pilot scope: One contract type and one governing jurisdiction; final legal interpretation and risk acceptance remain with qualified counsel. Implement one approved input format, a bounded representative case set and the first two task modules: upload legal documents for analysis; convert complex legal language into plain-language summaries. Support the next modules with operator review: detect potential risks and problematic terms; extract and highlight key clauses and terms. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.

After the MVP. Once paid pilots prove usefulness, automate repeatable reviewed steps and add one verified source integration. Expand supported inputs and case volume only after new evaluation cases pass. Build reusable customer configurations and recurring value reports around reviewed risk report linked to clause text. Retain the explicit scope boundary: One contract type and one governing jurisdiction; final legal interpretation and risk acceptance remain with qualified counsel.

What the build depends on. Document upload and preview, asynchronous analysis jobs, editable version history, reviewer access and tested export formats. High-fidelity legal review requires qualified counsel. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One contract type and one governing jurisdiction; final legal interpretation and risk acceptance remain with qualified counsel.

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

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.

Your brand, or this one

Run it under your own brand, or start from this concept style.

Selling it to your own clients: the go-to-market playbook

Pricing to test

Test a USD 300-1,500 fixed pilot for one defined contract package. Offer a monthly review allowance after repeat demand. Quote complex multi-jurisdiction or specialist regulatory review separately. These are test prices, not market benchmarks. Package the initial sale as one bounded reviewed risk report linked to clause text. Recurring fees must specify volume, review depth and integration support. For exchanges, test a disclosed coordination or successful-service fee rather than holding customer funds. Reprice only after measuring real delivery labor; platform-build cost is separate from a commercial pilot fee.

Message to test

Reduce manual reading while keeping every finding traceable to the clause it came from. Demonstrate a concrete reviewed risk report linked to clause text using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

In-house counsel, contract managers and small legal teams professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample reviewed risk report linked to clause text from a small authorized input set, with a transparent calculation of reviewed clauses per reviewer hour and material risks missed after sign-off and no promised savings.

The first 30 days

1. Week 1: interview five in-house counsel, contract managers and small legal teams reviewing agreements without full outside-counsel support and inspect a recent example of legal documents are long and complex, so reviewers miss risky terms, repeat manual reading and cannot show where a conclusion came from.
2. Week 2: prepare a consented or synthetic demonstration of the three task modules.
3. Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
4. Week 4: measure reviewed clauses per reviewer hour and material risks missed after sign-off, reviewer effort and repeat-purchase interest. This is a demand-validation plan, not a thirty-day full-product delivery promise.

Paid pilot

Agree quality and outcome thresholds before the pilot using this measure: Reviewed clauses per reviewer hour and material risks missed after sign-off. Continue only if the buyer accepts the actual output, the intended job outcome improves without unacceptable errors, and measured delivery cost fits willingness to pay. Revise or stop if access is unavailable, qualified review cannot be provided, or apparent savings disappear after corrections and support. Use held-out cases when comparing model quality; use a properly reviewed comparison design before making causal claims. Record missing cases and negative results alongside successful outputs.

Success metrics

Reviewed clauses per reviewer hour and material risks missed after sign-off; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs reviewed risk report linked to clause text. Retain permissioned settings and reviewed examples, report realized value honestly, and sell increased volume or adjacent approved workflows only after contribution margin and quality remain acceptable.

Why clients would pick it

A reusable library of approved playbooks, clause positions and review examples, together with reliable delivery for a narrow legal niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for in-house counsel, contract managers and small legal teams reviewing agreements without full outside-counsel support. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

LegalCheckPro, Docu, My Pocket Lawyer, SpeedLegal, FairPact AI, AI Contract Analysis, review.legal, Legalese Decoder, Detangle and Legal Graph. Compare this product with the buyer's present method on reviewed clauses per reviewer hour and material risks missed after sign-off. Offer a bounded paid workflow instead of claiming broad autonomous legal expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Model inference, document storage, reviewer hours, client revision rounds and licensed source material. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of reviewed risk report linked to clause text. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve legal privilege, source attribution, clause accuracy and usage permissions. Qualified counsel approve substantive conclusions and filing scope. One contract type and one governing jurisdiction; final legal interpretation and risk acceptance remain with qualified counsel. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.