# Purple

> AI legaltech build studio helping elite law firms discover, build, and take to market custom AI-powered legal technology.

Purple is an AI technology studio founded by ex-lawyers and technologists. We help law firms develop clear AI strategies, prototype and build custom legal technology products, and take them to market. Based in London, we work with Magic Circle, Silver Circle, and specialist firms globally.

Our framework has three phases: Discover (strategy and opportunity identification), Build (prototype and full platform development), and Go-To-Market (launch and scale). We build custom solutions - not off-the-shelf products. Clients own the IP.

## Core Principles

1. Law Informed, Product-Focused - team of ex-lawyers and technologists who de-risk the innovation journey
2. Aligned Incentives, Aligned Success - independent, no VC agenda, client success equals our success
3. Build Assets, Not Dependencies - client owns the IP, modular systems, no lock-in
4. Iterate Boldly, Learn Fast - lean startup methods applied to legaltech, rapid iteration

## Team

- Tim Pullan: Overall strategy, internal positioning, stakeholder interviews and leadership narrative. Extensive background as an AI venture builder in the legal domain over the past 10 years. Background as partner in 3 law firms.
- Dom Conte: AI opportunity narrative, design and positioning. One of the leading AI legaltech product designers in the UK market today, with a proven record of delivering highly successful products over the past 10 years. Also a highly experienced lawyer with expertise in planning and property law.
- Dmitry Selivanov: CTO and technical lead. Input on tooling, feasibility and build-vs-buy considerations. An AI applications specialist with a track record of building innovative and robust solutions inside and outside the legal sector.

## Services

### AI Strategy (4 weeks)

An evidence-led strategy sprint across five phases:

1. Listen (week 1) - stakeholder interviews across practice groups, knowledge, BD and IT; workflow analysis of how work actually moves through the firm; review of the tools and pilots already in flight
2. Assess (week 2) - AI maturity scored against a law-firm maturity model (data readiness, tooling, skills, governance, client posture); exposure analysis across the practice mix
3. Benchmark (weeks 2-3) - a market scan that separates deployed from announced: what peer firms actually run, what in-house teams now do themselves, where the vendor market is heading
4. Map (week 3) - an opportunity matrix scored on client value, feasibility and adoption risk; risks logged against each move; build, buy, partner or wait calls priced against real build costs
5. Decide (week 4) - a 6-12 month roadmap with owners named, governance and decision rights that fit a partnership, and the firm's external AI narrative

Deliverables: the partner paper (a concise strategy paper for the partnership), AI maturity assessment, opportunity map, and a sequenced 6-12 month roadmap.

### Discovery Sprint (6 weeks)

An evidence-led discovery sprint across five phases:

1. Ground (week 1) - AI product fundamentals taught by builders: what works today, what remains hype, and the product lens of problems before features
2. Map (week 2) - a four-hour workshop mapping friction in real workflows, reframed as How-Might-We product openings (8-10 defined opportunity areas)
3. Pressure-test (weeks 3-4) - six 45-minute stakeholder interviews validating assumptions against daily reality
4. Reality-check (week 5) - every surviving idea meets four questions: does the data exist, would users switch, can it be built inside a quarter, will someone pay
5. Prioritise (week 6) - a sixty-minute leadership session: ranked shortlist with scoring rationale and a 90-day plan with go and no-go checkpoints

Deliverables: discovery report, AI ideas pack (5-7 opportunities on single pages), 90-day quick-start plan.

### Innovation Accelerator (3-4 months)

A six-round structured innovation programme:

1. Launch and Inspiration (1 month) - firm-wide launch with training, templates, and guidance
2. Idea Shortlisting (2 days) - submissions assessed against problem definition, user value, strategic relevance, feasibility
3. Product Bootcamp (1 month) - kick-off workshop, founder mentoring, full product requirements documents
4. Prototyping (1 month) - Purple builds fully interactive prototypes with regular check-ins
5. Pitch Bootcamp (1 month) - commercial case development, market sizing, revenue models, ROI analysis
6. Demo Day (1 day) - 15-minute structured pitches to senior judging panel

### Workshops (half or full day)

Eleven workshops across four themes, built and delivered by people who ship AI products for law firms - run on the firm's own matters and data, not generic slides:

1. Foundational - AI & Product Fundamentals; From Innovation Theatre to Revenue; AI for Legal Leaders
2. Strategic - Build vs Buy; AI Positioning & Client Narrative; AI Economics for Law Firms
3. Practical - AI Hackathon (full day); Prompt Engineering for Lawyers; AI Product Design Sprint (full day)
4. Governance & Adoption - Responsible AI for Legal Practice; Driving Adoption

Workshops run standalone or bundled, in person or remote, and are tailored to the firm.

### Prototype (4 weeks)

Three phases to take an idea from concept to validated prototype:

1. Product Concept Workshop - define MVP experience, stakeholder alignment, user journey mapping, feature prioritisation
2. Rapid Agile Sprints - build functional interactive prototype, not wireframes
3. User and Client Validation - test with fee earners and trusted clients, gather feedback, usability analysis

Deliverables: MVP specification, interactive prototype, validation report, decision framework (proceed, pivot, or pause).

### Full Build (3-6 months)

Four phases from blueprint to production:

1. Expert Technical Blueprinting - system architecture, security framework, scalability planning, technology stack selection
2. Accelerated Development - core platform development using proprietary library of lawyer-trained AI agents
3. Co-Creation for Delivery - continuous iteration with fee earners, user acceptance testing, workflow optimisation
4. Deployment and Enablement - production deployment, security hardening, training programme delivery

Features: zero-trust architecture, field-level encryption, cloud-native infrastructure. Client owns the IP.

### Go-To-Market

Transform technology investment into market narrative. Create defensible revenue streams. Strategic launch and scale for legal technology products.

### Operating Model (ongoing)

SRA-compliant entity structuring for law firm tech spin-outs and AI offshoots:

1. Regulatory Assessment - map SRA requirements for your entity structure
2. Entity Design - define governance, ownership, and compliance framework
3. Operational Playbook - team roles, support models, escalation processes
4. Launch & Compliance - deploy the model with regulatory confidence

Deliverables: complete operating model document, regulatory-compliant entity structure, team structures and responsibilities, support and escalation frameworks, ongoing development plan.

### Business Planning (4-6 weeks)

Revenue models, pricing strategy, and partnership-ready commercial cases:

1. Market Analysis - competitive landscape, target segments, pricing benchmarks
2. Revenue Modelling - subscription, licensing, or hybrid models stress-tested against real data
3. Commercial Case - partnership-ready business plan with projections and assumptions
4. Go-To-Market Roadmap - phased launch plan with milestones and KPIs

Deliverables: detailed business plan with revenue projections, pricing framework for legal markets, competitive positioning analysis, phased go-to-market roadmap.

### GTM Sprint (6-8 weeks)

Launch execution sprint - sales enablement, pilot pipeline, pricing validation:

1. Sales Enablement - build the deck, scripts, and objection handling your team needs
2. Pilot Pipeline - identify and qualify 3-5 target prospects
3. Pricing Validation - test pricing with real prospects and iterate
4. Launch Collateral - marketing assets, positioning materials, and messaging framework
5. Launch Playbook - 90-day plan with milestones and go/no-go checkpoints

Deliverables: launch-ready sales deck, validated pricing, pilot pipeline of qualified prospects, marketing assets, 90-day launch playbook.

## Sectors

Purple builds sector-specific AI solutions for law firms. Each sector page (https://purple.law/sectors/) covers use cases, workflows, and example builds:

- Real Estate (https://purple.law/sectors/real-estate/): Automated lease monitoring and AI-powered property due diligence, built by former lawyers who understand property workflows.
- Banking & Finance (https://purple.law/sectors/banking-finance/): Automated covenant testing, facility monitoring, and loan documentation analysis.
- Corporate & M&A (https://purple.law/sectors/corporate-ma/): AI-powered due diligence, automated data room analysis, deal intelligence, and risk assessment.
- Litigation (https://purple.law/sectors/litigation/): Case outcome prediction, automated document review, and litigation cost modelling.
- Regulatory & Compliance (https://purple.law/sectors/regulatory-compliance/): Automated regulatory monitoring, compliance testing, and risk assessment.
- IP & Technology (https://purple.law/sectors/ip-technology/): Patent analysis, trademark monitoring, and technology transaction tools.
- Employment (https://purple.law/sectors/employment/): Automated tribunal analysis, settlement tools, and HR compliance monitoring.
- Environmental & Planning (https://purple.law/sectors/environmental-planning/): Automated planning analysis, environmental compliance, and regulatory monitoring.

## Resources

### The Missing Data Layer (white paper)

https://purple.law/resources/the-missing-data-layer/

Why AI in law firms fails on data, not tools - and how to build the foundation underneath it. Written for the innovation, technology and knowledge leaders of elite law firms. Covers:

- Why 52% of organisations cite data quality - not tools, regulation or skills - as their single biggest barrier to AI
- The three-tier data layer architecture (Raw, Organised, Derived) explained in plain terms
- The build-vs-buy technology spectrum: open-source lakehouse, Microsoft Fabric / Databricks, and SaaS
- The "vendor trap" - why letting Harvey or Legora own your data layer becomes a strategic dependency
- Three real strategies for getting started, and how to scope a first slice you can actually deliver

## The Future of Law (Purple's thesis)

https://purple.law/future-of-law/

Purple's strategic thesis on where the legal market is heading. The argument, in short:

- This is a structural shift, not another technology cycle. Previous waves of legal technology digitised the work around the law; the explosion of large language models lets the technology perform the work itself - reading the data room, drafting the first cut, applying the checklist. When technology changes who does the work, not just where it happens, it reprices the industry.
- Tools like Harvey and Legora are the leading edge of this, not the extent of it. What they prove is that legal work can now be performed by software at all; the repricing that follows is still mostly ahead of us.
- Firms are squeezed from several directions at once: client fee pressure, in-house AI, AI-native entrants, and rising talent cost against an eroding leverage model.
- The platforms firms buy are also the enabling layer for AI-native competitors. Orbital Witness launching Farringdon (a regulated legal services business) shows a technology company becoming a legal services provider; the same commercial gravity will act on other vendors that reach scale. An AI-native firm is a productised firm.
- Firms must fight on two fronts: defend the commoditisable base (the top of the funnel that feeds premium advisory - lose it and the pipeline starves) and build new productised revenue before someone else claims it. The billable hour will not refill lost revenue.
- The only scalable answer is to productise expertise - knowledge sold as products, bought repeatedly. Buying tools alone is not enough, because proprietary workflows embedded in a third-party platform compound someone else's asset, not yours.
- Three innovation models firms try: democratised innovation (give everyone the tools - rarely compounds, because billing incentives crowd out experimentation), the central innovation team (structurally boxed in, under-resourced and outside the commercial engine), and the external product partner - a dedicated subsidiary or venture with its own leadership, incentives and P&L (built to ship). The firm supplies expertise and market access; the product organisation is built to ship.
- This is the role Purple exists to play: a product foundry for law firms, run from operating design through to acting leadership of a firm's spin-out.
- Presented as a reasoned thesis, not a prediction: firms that productise create new markets; firms that do not drift toward commodity.

## Common Questions

### About Purple

**What does Purple do?**
Purple is an AI legaltech build studio. We help law firms discover where AI creates real value, build custom technology products, and take them to market. We are not a consultancy that hands over a slide deck - we design, prototype, build, and ship working products.

**What makes Purple different from other legaltech consultancies?**
Three things. First, we are founded by ex-lawyers who have built AI companies - we understand both sides. Second, we build custom products, not off-the-shelf tools. Every firm's workflows and client base are different, and the technology should reflect that. Third, you own the IP. We build it, you own it. No vendor lock-in, no recurring licence fees to us.

**Where is Purple based?**
London. The Ministry, 79-81 Borough Road, SE1 1DN. We work with firms across the UK and internationally.

### AI Strategy for Law Firms

**Why does our firm need an AI strategy?**
Clients increasingly expect firms to have a credible position on AI. Internally, leadership needs a clear lens for deciding where AI should be applied - and where it is noise. Without a strategy, firms either invest in the wrong areas, chase vendor pitches, or stall entirely. A strategy gives you a defensible position externally and clear direction internally.

**What does an AI strategy sprint involve?**
Five phases over four weeks. We interview across the partnership and map how work actually moves through the firm. We score your AI maturity against the market. We benchmark what peer firms actually run, not just announce. We map the opportunities and price the risks. Then we set the strategy - build, buy, partner or wait - with a 6-12 month roadmap, owners named and governance that fits a partnership.

**What is the difference between an AI Strategy and a Discovery Sprint?**
The AI Strategy answers the leadership question: where does AI create value for this firm, and what should we do about it - grounded in interviews, maturity scoring and market benchmarking, and ending in a roadmap the partnership can vote on. The Discovery Sprint is product-led - training, workshops and interviews that generate and validate specific AI product opportunities from within the firm. Many firms do the Strategy first, then the Sprint to go deeper on the shortlist.

### Building Legal Technology

**What is the difference between a Prototype and a Full Build?**
A Prototype is a four-week engagement that produces a functional, interactive model of your product. You can see it, click it, test it with users, and decide whether to proceed. A Full Build takes a validated prototype and turns it into a production-ready platform with enterprise-grade architecture, security, and deployment. The Prototype de-risks the decision. The Full Build delivers the asset.

**Do we own the IP?**
Yes. You own everything we build for you. No licence fees, no vendor lock-in, no recurring charges for using your own product. We build it, you own it.

**How do you handle data security and privacy?**
Security is built in from the start, not bolted on. Zero-trust architecture, field-level encryption, and cloud-native infrastructure that meets enterprise security requirements. We work with firms that handle highly sensitive client data, and our products are built to that standard.

### Working with Purple

**How much does it cost?**
It depends on the engagement. An AI Strategy sprint, a Discovery Sprint, a Prototype, and a Full Build are all different in scope and investment. We are transparent about pricing and will give you a clear figure before any engagement starts.

**Can we start with something small?**
Yes. The four-week AI Strategy sprint or a Prototype are both designed as focused, bounded engagements. They give you real output and a clear decision point without committing to a large programme upfront.

**What size of firm do you work with?**
We work with Magic Circle, Silver Circle, and specialist firms. The common thread is ambition - firms that want to use AI strategically, not just adopt tools for the sake of it.

### AI in Legal Services

**Is AI going to replace lawyers?**
No. AI is going to change how legal services are delivered, priced, and experienced by clients. The firms that use AI well will deliver better outcomes faster and more profitably. The firms that ignore it will gradually lose competitive position. But the expertise, judgment, and client relationships that lawyers bring are not being replaced - they are being amplified.

**What are AI-native law firms?**
Businesses built from the ground up with AI at the core of their delivery model. They do not bolt AI onto traditional workflows - they design workflows around AI capabilities. They tend to offer productised services, transparent pricing, and technology-first delivery. They are emerging fast, and they are competing for the same clients and talent as traditional firms.

**Should we build or buy our legal AI tools?**
It depends on how central the capability is to your competitive positioning. If every firm in your market can buy the same tool, it creates parity, not advantage. For undifferentiated needs - general research, basic document review - off-the-shelf tools are fine. For capabilities that define how you serve clients or win work, building something proprietary creates defensible value. The answer is usually a mix of both.

**How do we get lawyers to actually use AI tools?**
Build with them, not for them. The number one reason AI tools fail in law firms is that they were designed without involving the people who need to use them. Our build process includes fee earners from day one - co-creation sessions, user testing, workflow integration. If the tool fits how lawyers actually work, adoption follows.

## Contact

- Email: hello@purple.law
- Website: https://purple.law
- Location: The Ministry, 79-81 Borough Road, London, SE1 1DN