Made byBobr AI

Reor: AI Forensic Reasoning for Legal Teams

Discover how Reor uses AI forensic reasoning to automate document review for litigation, insolvency, and M&A, turning complex data rooms into cited evidence.

#pitch-deck#legal-ai#startup#forensic-reasoning#legal-tech#document-review#seed-funding
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Pitch
CONFIDENTIAL INVESTOR PRESENTATION

Reor

Forensic reasoning for the legal stack.

Turn complex data rooms into evidence-backed answers in hours, not weeks.

Seeking £1.5m seed funding
May 2026
Made byBobr AI
THE PROBLEM

The legal work that still runs on human reading.

Complex legal matters — disputes, insolvencies, M&A diligence, investigations — depend on legal teams reading thousands of documents. Board minutes, emails, contracts, recordings, correspondence. The bottleneck is not knowing which questions to ask. Partners know that. The bottleneck is finding every answer, across every document, fast enough to matter.

Junior associates spend weeks in data rooms. Evidence is fragmented. Key facts are buried. The most expensive lawyers in the room spend their time waiting for the document review to be done before the real work can begin.

240+
average hours spent on document review in a complex matter
£50k+
typical associate cost for a large document review
1 in 5
key facts missed in manual large-document reviews
Made byBobr AI
THE PROBLEM

Expensive. Slow. Risky.

£

Expensive

Partner-led teams and junior associates spend weeks reviewing documents. At £300-£800/hour blended rates, large matter document review costs tens of thousands before any substantive work begins.

  • Human reading speed is the primary cost driver
  • Associates' time is consumed by discovery, not analysis
48h+

Slow

Timelines are constrained by human review speed. A 3,000-document data room can take 2-4 weeks to review meaningfully. In disputes and restructuring, time is not a luxury.

  • Critical decisions delayed by review cycles
  • Urgency of disputes demands faster answers
!

Risky

Missed evidence, unspotted contradictions and late-discovered documents change outcomes. Manual review at scale is inherently incomplete. One missed board minute or overlooked email can alter a case.

  • Key evidence buried across thousands of files
  • Fragmented sources — emails, contracts, recordings
Made byBobr AI
MARKET TIMING

The category has been validated. The next layer is reasoning.

Harvey AI raised over $300m. Robin AI has built a credible contract review business. Legal AI is no longer a category risk — it is a category opportunity. Summarisation and drafting are now accepted. The next valuable layer is forensic reasoning: hypothesis-driven evidence analysis across entire matters.

Foundation models, OCR, long-context reasoning and secure enterprise deployment are now capable enough to support this. The infrastructure exists. What has been missing is the product and legal domain expertise to apply it to complex matter work.

Reor is built for this moment.

HARVEY AI
Raised $300m+. Proves enterprise legal AI is a viable, large-scale category.
ROBIN AI
Contract review and automation — already commercial. Proves law firms and in-house teams will pay for AI-assisted legal work.
FOUNDATION MODELS
Long-context reasoning, OCR pipelines and semantic search now production-ready for enterprise legal use cases.
REOR'S TIMING
Drafting and summarisation are commoditising. The defensible, high-value layer is forensic reasoning. That window is open now.
Made byBobr AI
THE PRODUCT

A forensic reasoning engine for the legal stack.

01
Upload Data Room
Documents, emails, contracts, board notes, recordings, transcripts
02
Extract & Classify
OCR, per-document summary, entity/date/obligation tagging, red flag detection
03
Build Evidence Graph
Entities, people, companies, dates, obligations and events mapped and indexed
04
Pose Hypothesis
Legal team asks a question or states a forensic hypothesis
05
Receive Cited Answer
Timeline, evidence pack, supporting and contradictory sources, cited findings
Hypothesis-driven, not passive Q&A
Semantic search across entire corpus
Contradiction and inconsistency detection
Entity and relationship mapping
Timeline construction
Source citations back to original documents
Human-in-the-loop by design
Privilege and confidentiality aware
Made byBobr AI
LIVE USE CASE

Product in practice.

Real matter. Real documents. Real findings.

In April 2026, Reor was used on a live complex legal matter involving a data room of approximately 3,000 documents — board minutes, emails, contracts, shareholder records and recordings.

The Forensic Hypothesis Posited

"Did certain investors act as creditors rather than shareholders, and is there evidence of a strategy to force administration or acquire control?"

Reor processed the corpus, mapped entities, built a timeline and surfaced supporting and contradictory evidence — with source citations.

£8,000 revenue generated. £2,000/month expected ongoing.
01.
Ingested and classified 3,000+ documents
02.
Mapped entities: people, companies, dates, obligations
03.
Built a timeline of investor, board and corporate events
04.
Identified board notes, emails and contracts supporting the hypothesis
05.
Produced a cited findings pack with contradictory evidence flagged

The output gave the legal team weeks of analysis in hours — with every finding traceable to source.

Made byBobr AI
APPLICATIONS

Built for the most complex legal work.

Forensic Analysis

Patterns of behaviour, intent and control. Asset movement, related-party issues, collusion indicators and hidden relationships across large document sets.

Litigation Support

Chronology building, evidence mapping, claim support, contradiction discovery and witness preparation materials. Find the facts before opposing counsel does.

Insolvency and Restructuring

Director conduct analysis, creditor and shareholder mapping, administration preparation, disputed control and evidence of value destruction.

M&A and Investment Diligence

Ownership structures, IP commitments, change-of-control triggers, commercial dependencies and hidden regulatory or contractual risk.

Corporate Investigations

Internal investigations, whistleblower support, misconduct mapping, governance issues and board-level conduct review.

Complex Commercial Risk

Cascading obligations, contract dependencies, breach scenarios and exposure modelling across large commercial document portfolios.

In every case, the answer is distributed across hundreds or thousands of documents. Reor finds it.

Made byBobr AI
TRACTION

Live revenue. Real product. Working use case.

This is not a prototype looking for a problem. It is a working product that has already earned revenue on a complex legal matter.

£8,000
Revenue in April 2026
From a single live complex legal matter
£2,000
Expected monthly recurring
From the same ongoing matter
~3,000
Documents processed
Board notes, emails, contracts and recordings in a live data room
1
Live complex matter
Forensic hypothesis tested, evidence mapped, findings produced
Working product, not slideware
OCR, extraction, entity mapping and citation engine operational
Legal hypothesis tested on a real insolvency/control dispute matter
Findings delivered to legal team with source citations
Senior legal contact in New York with visibility of the work
Potential to open US legal network and funding conversations
Spun out from GreenDoorAI Ltd to focus exclusively on legal/forensic AI
Founding team with combined AI engineering and enterprise commercial experience
Made byBobr AI
COMPETITIVE POSITION

Reor is the forensic reasoning layer.

Existing tools solve drafting, summarisation and document search. None are built for hypothesis-driven forensic reasoning over complex matter corpora.

TOOL / CATEGORY PRIMARY FOCUS CORE STRENGTH KEY GAP REOR'S POSITION
Harvey AI Broad legal AI platform Drafting, research, enterprise workflow automation Not designed for forensic hypothesis testing or evidence chain analysis Category proof — enterprise legal AI works at scale
Robin AI Contract review and lifecycle Contract analysis, drafting, CLM Contract-level intelligence, not matter-level forensic reasoning Category proof — law firms pay for AI contract work
eDiscovery (Relativity, Nuix etc.) Document review and production Large-scale document processing and review management Search and production, not reasoning or hypothesis testing Complementary — Reor reasons over what eDiscovery surfaces
Generic LLM wrappers Q&A and summarisation over documents Fast, flexible, cheap No evidence chains, no hypothesis logic, no legal domain structure Reor adds legal reasoning architecture, not just retrieval
Reor Forensic reasoning engine Hypothesis testing, evidence chains, timelines, citations, complex matter intelligence The missing layer: forensic reasoning for complex legal work

Harvey and Robin validate the category. Reor occupies a distinct and defensible position within it.

Made byBobr AI
BUSINESS MODEL

Revenue from day one. Three clear monetisation paths.

Matter-Based Fees

Per engagement
£5,000 – £25,000

Charged per data room or matter engagement. Sized by document volume and complexity. Applicable to litigation, insolvency, M&A diligence and investigations.

  • Immediate ROI versus associate cost
  • High urgency means low price sensitivity
  • Natural entry point for design partners

Platform Subscription

Monthly firm or team licence
£2,000 – £10,000/mo

For law firms, litigation boutiques, insolvency practices and corporate legal teams with recurring complex matter volume. Includes matter workspace, collaboration tools and priority processing.

  • Predictable recurring revenue
  • Grows with matter volume
  • Pathway to enterprise accounts

Enterprise and Private Deployment

Bespoke and secure
Custom / £100k+ pa

For large law firms, banks, litigation funders and corporate legal departments requiring on-premise or private cloud deployment. Includes custom workflows, audit trails and privilege-aware architecture.

  • Highest contract value
  • Competitive moat through deep integration
  • Priority for year 2 and beyond
CURRENT PROOF
£8,000 in April 2026 from a single matter. £2,000/month expected recurring. Early validation that the matter-based model works.
PATHWAY
5 design partner matters at £10k average = £50k. Convert to subscriptions at £3k/month each = £180k ARR. Add enterprise — path to £1m ARR within 18 months.
Made byBobr AI
GO-TO-MARKET

Network-led. Hypothesis-proven. Scaling through credibility.

Legal market entry requires trust and domain credibility. Our go-to-market mirrors how serious legal work is won — through relationships, results and reputation.

01
0-6 MONTHS

Design Partners and Legal Network

Founder-led sales into known legal network. Target: 3-5 design partners across litigation boutiques, insolvency practices and restructuring advisers. Focus on high-value, urgent matters where ROI is immediate. Convert current matter into reference case.

Litigation firms · Insolvency practitioners · Restructuring advisers · Corporate counsel
02
6-12 MONTHS

Practice Group Expansion

Expand via warm referrals into M&A teams, compliance functions and corporate legal departments. Build thought leadership around forensic reasoning, AI evidence chains and data room intelligence. Establish advisory panel of senior legal names.

M&A practices · General counsel offices · Litigation funders · Private equity legal teams
03
12-18 MONTHS

Enterprise and Platform

Move upstream into large law firm practice groups and corporate legal departments. Enterprise deployment with security, audit and privilege architecture. Partner integrations with eDiscovery and legal workflow platforms.

Magic Circle and Silver Circle firms · Big Four forensic teams · US law firm UK offices · Litigation funders

THOUGHT LEADERSHIP

Position Reor as the authority on forensic reasoning for legal teams. Publish on AI evidence chains, data room intelligence and complex matter AI.

US NETWORK

Senior legal contact in New York with proximity to the forensic work. Potential to open US legal and funding conversations.

Made byBobr AI
ROADMAP

From live traction to repeatable legal AI platform.

0–3 Months
Harden and Validate
  • Productise current forensic workflow
  • Complete current live matter
  • Build repeatable OCR/extraction pipeline
  • Document and systemise hypothesis testing
  • Lock in first design partner
3–6 Months
Build and Deepen
  • Launch design partner programme (3-5 firms)
  • Build evidence graph and entity mapping v2
  • Improve citation UI and findings export
  • Secure workspace and access controls
  • Build litigation and insolvency matter templates
6–12 Months
Scale and Secure
  • Enterprise security and audit trail
  • Collaboration features for legal teams
  • Exportable findings packs and court-ready output
  • Matter template library — 3 priority use cases
  • Reach £250k ARR or equivalent run-rate
  • Form legal advisory panel
12–18 Months
Platform and Expand
  • Multi-jurisdiction legal corpora
  • Advanced reasoning and workflow automation
  • Enterprise partner integrations
  • 20-30 paying firms or legal teams
  • £1m+ ARR or revenue run-rate
  • Prepare Series A narrative
Every milestone is anchored to a paying use case, not a feature roadmap.
Made byBobr AI
USE OF FUNDS

£1.5m to convert live traction into a repeatable legal AI business.

18-month runway. Five focused workstreams. Every pound tied to a commercial outcome.

40%
Product and Engineering
Robust ingestion pipeline, OCR, evidence graph, citation engine, secure workspace and collaboration features
15%
Legal Domain Expertise
Legal advisors, matter workflow design, domain validation and QA processes
15%
Security and Compliance
Data protection, audit trails, privilege-aware architecture and private/secure deployment options
20%
Go-to-Market
Founder-led sales, legal network development, design partner programme, thought leadership and events
10%
Operations and Delivery
Customer onboarding, data processing workflows, matter delivery support and team operations
£1.5m
Seed raise target
18-month runway
Founder equity
Richard Heyns 60% / Stephen McGhie 40% pre-investment
Standalone entity
Spin-out from GreenDoorAI Ltd — legal/forensic AI to operate as standalone entity

The largest allocation is product and engineering. We are building a serious technical product, not a reskinned wrapper. The second priority is go-to-market — we have the network and the early proof. Now we need to execute at scale.

Made byBobr AI
TEAM

Two founders. Complementary expertise. Built the first version already.

RH

Richard Heyns

Co-Founder and CEO / Technical Lead
Creator of GreenDoorAI and the first forensic AI product
AI engineering, product development and system architecture
Built the OCR, extraction, evidence graph and hypothesis testing engine used on the first live legal matter
Combines technical depth with product judgement
SM

Stephen McGhie

Co-Founder and CRO / Commercial Lead
Enterprise sales, product positioning and go-to-market strategy
Investor narrative, commercial structuring and partnership development
Background in enterprise software and complex B2B sales
Leads commercial relationships, fundraising and strategic conversations
LEGAL ADVISORY BOARD
To be formed with senior legal practitioners in litigation, insolvency, restructuring and M&A. We are actively seeking advisors with legal market access and credibility.
WHAT WE ARE SEEKING
Strategic capital with legal market access. Introductions to design partner law firms. Advisors who can accelerate credibility with senior legal buyers.
Made byBobr AI
THE OPPORTUNITY

Reor is building the forensic reasoning layer for complex legal work.

We have a working product, live revenue and a validated use case on a real complex legal matter. The legal AI category is proven. The forensic reasoning layer is not yet occupied. We are raising £1.5m to convert this traction into a repeatable, scalable legal AI business.

£1.5m seed funding — 18-month runway, product, team and go-to-market
Strategic advisors with legal market access and credibility
Design partner introductions — litigation, insolvency, M&A and investigations
If you understand complex legal work, you know how much time is spent finding answers. Reor finds them faster.
reor.ai | hello@reor.ai
£1.5m
Seed Round
May 2026
Confidential
Made byBobr AI
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Reor: AI Forensic Reasoning for Legal Teams

Discover how Reor uses AI forensic reasoning to automate document review for litigation, insolvency, and M&A, turning complex data rooms into cited evidence.

CONFIDENTIAL INVESTOR PRESENTATION

Reor

Forensic reasoning for the legal stack.

Turn complex data rooms into evidence-backed answers in hours, not weeks.

Seeking £1.5m seed funding

May 2026

THE PROBLEM

The legal work that still runs on human reading.

Complex legal matters — disputes, insolvencies, M&A diligence, investigations — depend on legal teams reading thousands of documents. Board minutes, emails, contracts, recordings, correspondence. The bottleneck is not knowing which questions to ask. Partners know that. The bottleneck is finding every answer, across every document, fast enough to matter.

Junior associates spend weeks in data rooms. Evidence is fragmented. Key facts are buried. The most expensive lawyers in the room spend their time waiting for the document review to be done before the real work can begin.

240+

average hours spent on document review in a complex matter

£50k+

typical associate cost for a large document review

1 in 5

key facts missed in manual large-document reviews

THE PROBLEM

Expensive. Slow. Risky.

£

Expensive

Partner-led teams and junior associates spend weeks reviewing documents. At £300-£800/hour blended rates, large matter document review costs tens of thousands before any substantive work begins.

Human reading speed is the primary cost driver

Associates' time is consumed by discovery, not analysis

48h+

Slow

Timelines are constrained by human review speed. A 3,000-document data room can take 2-4 weeks to review meaningfully. In disputes and restructuring, time is not a luxury.

Critical decisions delayed by review cycles

Urgency of disputes demands faster answers

!

Risky

Missed evidence, unspotted contradictions and late-discovered documents change outcomes. Manual review at scale is inherently incomplete. One missed board minute or overlooked email can alter a case.

Key evidence buried across thousands of files

Fragmented sources — emails, contracts, recordings

MARKET TIMING

The category has been validated. The next layer is reasoning.

Harvey AI raised over $300m. Robin AI has built a credible contract review business. Legal AI is no longer a category risk — it is a category opportunity. Summarisation and drafting are now accepted. The next valuable layer is forensic reasoning: hypothesis-driven evidence analysis across entire matters.

Foundation models, OCR, long-context reasoning and secure enterprise deployment are now capable enough to support this. The infrastructure exists. What has been missing is the product and legal domain expertise to apply it to complex matter work.

Reor is built for this moment.

HARVEY AI

Raised $300m+. Proves enterprise legal AI is a viable, large-scale category.

ROBIN AI

Contract review and automation — already commercial. Proves law firms and in-house teams will pay for AI-assisted legal work.

FOUNDATION MODELS

Long-context reasoning, OCR pipelines and semantic search now production-ready for enterprise legal use cases.

REOR'S TIMING

Drafting and summarisation are commoditising. The defensible, high-value layer is forensic reasoning. That window is open now.

THE PRODUCT

A forensic reasoning engine for the legal stack.

Upload Data Room

Documents, emails, contracts, board notes, recordings, transcripts

Extract & Classify

OCR, per-document summary, entity/date/obligation tagging, red flag detection

Build Evidence Graph

Entities, people, companies, dates, obligations and events mapped and indexed

Pose Hypothesis

Legal team asks a question or states a forensic hypothesis

Receive Cited Answer

Timeline, evidence pack, supporting and contradictory sources, cited findings

Hypothesis-driven, not passive Q&A

Semantic search across entire corpus

Contradiction and inconsistency detection

Entity and relationship mapping

Timeline construction

Source citations back to original documents

Human-in-the-loop by design

Privilege and confidentiality aware

LIVE USE CASE

Product in practice.

Real matter. Real documents. Real findings.

In April 2026, Reor was used on a live complex legal matter involving a data room of approximately 3,000 documents — board minutes, emails, contracts, shareholder records and recordings.

Did certain investors act as creditors rather than shareholders, and is there evidence of a strategy to force administration or acquire control?

Reor processed the corpus, mapped entities, built a timeline and surfaced supporting and contradictory evidence — with source citations.

£8,000 revenue generated. £2,000/month expected ongoing.

Ingested and classified 3,000+ documents

Mapped entities: people, companies, dates, obligations

Built a timeline of investor, board and corporate events

Identified board notes, emails and contracts supporting the hypothesis

Produced a cited findings pack with contradictory evidence flagged

The output gave the legal team weeks of analysis in hours — with every finding traceable to source.

APPLICATIONS

Built for the most complex legal work.

Forensic Analysis

Patterns of behaviour, intent and control. Asset movement, related-party issues, collusion indicators and hidden relationships across large document sets.

Litigation Support

Chronology building, evidence mapping, claim support, contradiction discovery and witness preparation materials. Find the facts before opposing counsel does.

Insolvency and Restructuring

Director conduct analysis, creditor and shareholder mapping, administration preparation, disputed control and evidence of value destruction.

M&A and Investment Diligence

Ownership structures, IP commitments, change-of-control triggers, commercial dependencies and hidden regulatory or contractual risk.

Corporate Investigations

Internal investigations, whistleblower support, misconduct mapping, governance issues and board-level conduct review.

Complex Commercial Risk

Cascading obligations, contract dependencies, breach scenarios and exposure modelling across large commercial document portfolios.

In every case, the answer is distributed across hundreds or thousands of documents. Reor finds it.

TRACTION

Live revenue. Real product. Working use case.

This is not a prototype looking for a problem. It is a working product that has already earned revenue on a complex legal matter.

£8,000

Revenue in April 2026

From a single live complex legal matter

£2,000

Expected monthly recurring

From the same ongoing matter

~3,000

Documents processed

Board notes, emails, contracts and recordings in a live data room

1

Live complex matter

Forensic hypothesis tested, evidence mapped, findings produced

Working product, not slideware

OCR, extraction, entity mapping and citation engine operational

Legal hypothesis tested on a real insolvency/control dispute matter

Findings delivered to legal team with source citations

Senior legal contact in New York with visibility of the work

Potential to open US legal network and funding conversations

Spun out from GreenDoorAI Ltd to focus exclusively on legal/forensic AI

Founding team with combined AI engineering and enterprise commercial experience

COMPETITIVE POSITION

Reor is the forensic reasoning layer.

Existing tools solve drafting, summarisation and document search. None are built for hypothesis-driven forensic reasoning over complex matter corpora.

TOOL / CATEGORY

PRIMARY FOCUS

CORE STRENGTH

KEY GAP

REOR'S POSITION

Harvey AI

Broad legal AI platform

Drafting, research, enterprise workflow automation

Not designed for forensic hypothesis testing or evidence chain analysis

Category proof — enterprise legal AI works at scale

Robin AI

Contract review and lifecycle

Contract analysis, drafting, CLM

Contract-level intelligence, not matter-level forensic reasoning

Category proof — law firms pay for AI contract work

eDiscovery (Relativity, Nuix etc.)

Document review and production

Large-scale document processing and review management

Search and production, not reasoning or hypothesis testing

Complementary — Reor reasons over what eDiscovery surfaces

Generic LLM wrappers

Q&A and summarisation over documents

Fast, flexible, cheap

No evidence chains, no hypothesis logic, no legal domain structure

Reor adds legal reasoning architecture, not just retrieval

Reor

Forensic reasoning engine

Hypothesis testing, evidence chains, timelines, citations, complex matter intelligence

The missing layer: forensic reasoning for complex legal work

Harvey and Robin validate the category. Reor occupies a distinct and defensible position within it.

BUSINESS MODEL

Revenue from day one. Three clear monetisation paths.

Matter-Based Fees

Per engagement

£5,000 – £25,000

Charged per data room or matter engagement. Sized by document volume and complexity. Applicable to litigation, insolvency, M&A diligence and investigations.

Immediate ROI versus associate cost

High urgency means low price sensitivity

Natural entry point for design partners

Platform Subscription

Monthly firm or team licence

£2,000 – £10,000/mo

For law firms, litigation boutiques, insolvency practices and corporate legal teams with recurring complex matter volume. Includes matter workspace, collaboration tools and priority processing.

Predictable recurring revenue

Grows with matter volume

Pathway to enterprise accounts

Enterprise and Private Deployment

Bespoke and secure

Custom / £100k+ pa

For large law firms, banks, litigation funders and corporate legal departments requiring on-premise or private cloud deployment. Includes custom workflows, audit trails and privilege-aware architecture.

Highest contract value

Competitive moat through deep integration

Priority for year 2 and beyond

CURRENT PROOF

£8,000 in April 2026 from a single matter. £2,000/month expected recurring. Early validation that the matter-based model works.

PATHWAY

5 design partner matters at £10k average = £50k. Convert to subscriptions at £3k/month each = £180k ARR. Add enterprise — path to £1m ARR within 18 months.

GO-TO-MARKET

Network-led. Hypothesis-proven. Scaling through credibility.

Legal market entry requires trust and domain credibility. Our go-to-market mirrors how serious legal work is won — through relationships, results and reputation.

01

0-6 MONTHS

Design Partners and Legal Network

Founder-led sales into known legal network. Target: 3-5 design partners across litigation boutiques, insolvency practices and restructuring advisers. Focus on high-value, urgent matters where ROI is immediate. Convert current matter into reference case.

Litigation firms · Insolvency practitioners · Restructuring advisers · Corporate counsel

02

6-12 MONTHS

Practice Group Expansion

Expand via warm referrals into M&A teams, compliance functions and corporate legal departments. Build thought leadership around forensic reasoning, AI evidence chains and data room intelligence. Establish advisory panel of senior legal names.

M&A practices · General counsel offices · Litigation funders · Private equity legal teams

03

12-18 MONTHS

Enterprise and Platform

Move upstream into large law firm practice groups and corporate legal departments. Enterprise deployment with security, audit and privilege architecture. Partner integrations with eDiscovery and legal workflow platforms.

Magic Circle and Silver Circle firms · Big Four forensic teams · US law firm UK offices · Litigation funders

THOUGHT LEADERSHIP

Position Reor as the authority on forensic reasoning for legal teams. Publish on AI evidence chains, data room intelligence and complex matter AI.

US NETWORK

Senior legal contact in New York with proximity to the forensic work. Potential to open US legal and funding conversations.

ROADMAP

From live traction to repeatable legal AI platform.

0–3 Months

Harden and Validate

Productise current forensic workflow

Complete current live matter

Build repeatable OCR/extraction pipeline

Document and systemise hypothesis testing

Lock in first design partner

3–6 Months

Build and Deepen

Launch design partner programme (3-5 firms)

Build evidence graph and entity mapping v2

Improve citation UI and findings export

Secure workspace and access controls

Build litigation and insolvency matter templates

6–12 Months

Scale and Secure

Enterprise security and audit trail

Collaboration features for legal teams

Exportable findings packs and court-ready output

Matter template library — 3 priority use cases

Reach £250k ARR or equivalent run-rate

Form legal advisory panel

12–18 Months

Platform and Expand

Multi-jurisdiction legal corpora

Advanced reasoning and workflow automation

Enterprise partner integrations

20-30 paying firms or legal teams

£1m+ ARR or revenue run-rate

Prepare Series A narrative

Every milestone is anchored to a paying use case, not a feature roadmap.

USE OF FUNDS

£1.5m to convert live traction into a repeatable legal AI business.

18-month runway. Five focused workstreams. Every pound tied to a commercial outcome.

40%

Product and Engineering

Robust ingestion pipeline, OCR, evidence graph, citation engine, secure workspace and collaboration features

15%

Legal Domain Expertise

Legal advisors, matter workflow design, domain validation and QA processes

15%

Security and Compliance

Data protection, audit trails, privilege-aware architecture and private/secure deployment options

20%

Go-to-Market

Founder-led sales, legal network development, design partner programme, thought leadership and events

10%

Operations and Delivery

Customer onboarding, data processing workflows, matter delivery support and team operations

£1.5m

Seed raise target

18-month runway

Founder equity

Richard Heyns 60% / Stephen McGhie 40% pre-investment

Standalone entity

Spin-out from GreenDoorAI Ltd — legal/forensic AI to operate as standalone entity

The largest allocation is product and engineering. We are building a serious technical product, not a reskinned wrapper. The second priority is go-to-market — we have the network and the early proof. Now we need to execute at scale.

TEAM

Two founders. Complementary expertise. Built the first version already.

RH

Richard Heyns

Co-Founder and CEO / Technical Lead

Creator of GreenDoorAI and the first forensic AI product

AI engineering, product development and system architecture

Built the OCR, extraction, evidence graph and hypothesis testing engine used on the first live legal matter

Combines technical depth with product judgement

SM

Stephen McGhie

Co-Founder and CRO / Commercial Lead

Enterprise sales, product positioning and go-to-market strategy

Investor narrative, commercial structuring and partnership development

Background in enterprise software and complex B2B sales

Leads commercial relationships, fundraising and strategic conversations

LEGAL ADVISORY BOARD

To be formed with senior legal practitioners in litigation, insolvency, restructuring and M&A. We are actively seeking advisors with legal market access and credibility.

WHAT WE ARE SEEKING

Strategic capital with legal market access. Introductions to design partner law firms. Advisors who can accelerate credibility with senior legal buyers.

THE OPPORTUNITY

Reor is building the forensic reasoning layer for complex legal work.

We have a working product, live revenue and a validated use case on a real complex legal matter. The legal AI category is proven. The forensic reasoning layer is not yet occupied. We are raising £1.5m to convert this traction into a repeatable, scalable legal AI business.

£1.5m seed funding — 18-month runway, product, team and go-to-market

Strategic advisors with legal market access and credibility

Design partner introductions — litigation, insolvency, M&A and investigations

If you understand complex legal work, you know how much time is spent finding answers. Reor finds them faster.

reor.ai

hello@reor.ai

£1.5m

Seed Round

May 2026

Confidential