OVERVIEW
LEGALFAB.AI
The central nervous systems for the connected enterprise
The Challenge
The Need
Our Mission
Our Edge
Market Traction
Funding
Team
Benefits

The Challenge

Fragmented legacy systems and disconnected point solutions, often masked as “AI transformation.”
Critical data is siloed across the organization, limiting visibility, coordination, and real-time decision-making.
Transformation is slow and costly, with complex programs often taking 18+ months to deliver limited impact.
High integration overhead and duplicated systems reduce agility and scalability at enterprise level.
Rising regulatory, market, and customer pressures expose the limits of manual, reactive, and human-dependent workflows.
The result is a widening gap between the need for real-time intelligent operations and the reality of fragmented enterprise architecture.

The Need

Enterprises require a unified intelligent layer that connects fragmented systems and enables end-to-end operational visibility.
A real-time data foundation that resolves entities, eliminates duplication, and breaks down silos across the organization.
Infrastructure that enables continuous compliance, monitoring, and governance at scale.
Autonomous, proactive workflows that move operations from reactive execution to intelligent decisioning.
Explainable, auditable, domain-aware AI that operates safely in complex, regulated environments.
Solutions that deliver immediate, measurable ROI without long transformation cycles or heavy system replacement.

Our Mission

LegalFab is redefining how enterprises operate in the age of AI.
Our platform unifies enterprise data, powers intelligent agents, and embeds governance into every workflow. Organizations use LegalFab to automate complex decisions, uncover hidden relationships, stay ahead of risk and identify opportunities in an increasingly dynamic world. By combining graph-native intelligence with agentic AI, we are creating a new operating model for enterprises; one that is intelligent, autonomous, and trusted by design.

Our Edge

LegalFab is not another AI application it is the infrastructure for trusted enterprise intelligence.
Built on a unique three-layer architecture: Knowledge Fabric, Agentic Studio, and Agentic Utilities. We unify enterprise data without migration, orchestrate explainable AI agents without code, and embed governance into every action. The platform delivers deterministic reasoning, real-time entity resolution, and enterprise-scale automation from day one. LegalFab was designed from the ground up for autonomous, trusted, and continuously evolving enterprise operations.

Market Traction & Early Adopters

German Law Firm- Fabric & Agentic automation of workflows
Tier 1 UK Law Firm- End to End Platform pilot
Tier 1 Commercial Partners
Deployment & Integration partner
Big 4 Managed Service Partner

Funding

Self funded & Angel investors
Actively raising round A

Team

Elinoar Sofer
CEO

An entrepreneur with deep-rooted experience in the global technology ecosystem. Specialized in the strategic leadership and operational scaling of enterprise startups, combining a visionary growth mindset with the tactical discipline required to dominate emerging markets.

Simon Thompson
COO

A leading expert in legal-tech operations and digital transformation. As a former CIO/COO, they bring unparalleled insight into the industry’s technical and operational bottlenecks, providing the strategic roadmap for sustainable, tech-enabled growth.

Thomas Kohlmeier
CCO

A legal professional turned venture builder with deep-sector expertise in navigating the intersection of law, insurance, and fintech. Proven track record in scaling high-growth startups by identifying untapped market opportunities and engineering complex, multi-industry commercial strategies.

Alex Shereshevsky
CTO

A visionary technologist and entrepreneur with a track record of bridging the gap between high-level theory and enterprise utility. Expert in engineering complex algorithmic frameworks into actionable, high-value intelligence. Designed and developed advanced LLMs.

Measurable Business Benefits

Complete unification of data silos
X Faster implementation (months Vs Years)
Order of magnitude lower TCO
Replace third‑party dependence; Firms build their own bespoke, domain‑specific agents
Lower maintenance burden
New revenue Opportunities
Private & Confidential — Prepared for ARAG
02
PLATFORM ARCHITECTURE
LegalFab · Platform Architecture

The Knowledge Fabric

A defensible core, wrapped in concentric layers — components, output, and ecosystem.

Knowledge
Fabric
◉ CORE
Layer 3
Fabric Ecosystem
Layer 2
Fabric Output
Layer 1
Fabric Components
Layer 1 · Components

Fabric Components

The capabilities that make up the Fabric core.
Source connectionOSINT connectionsDiscovery serviceLineageEntity resolutionQuality metricsActive metadataSchema managementOntology management
Layer 2 · Output

Fabric Output

What the Fabric produces from those components.
Knowledge GraphNORA & reasoningData catalogueObservabilityGovernanceFederated searchData unificationAgentic data layer
Layer 3 · Ecosystem

Fabric Ecosystem

Built on top of the Fabric — the studios and the agents that run on it.
Studios
Agentic StudioMCP Studio
Private & Confidential — Prepared for ARAG
03
PLATFORM ARCHITECTURE
Layer 4 · Levels of Automation

Agent Types & AI Autonomy

The outer ring runs agents at five autonomy levels — from fully deterministic (0) to fully autonomous, AGI-grade reasoning (4). Each level trades human determinism for AI autonomy.

0
L0 · BPM-Governed
BPM-Governed Agents

Autonomy bounded by a defined BPM process — the agent acts freely within the steps and gates of a modelled business process.

1
L1 · Supervised
Human-in-the-Middle

ReAct reasoning with a human in the loop — AI proposes, a person reviews and approves at each decision point.

2
L2 · Self-Organising
Self-Organising Graph

DAG agents that self-organise from user-defined rules & dependencies — plan their own path, escalate on exceptions.

3
L3 · Deterministic
Deterministic Agents

Follow predefined, fixed steps. No reasoning autonomy — fully predictable and repeatable.

4
L4 · Autonomous
Pure Agentic (AGI)

ReAct, fully autonomous — sets its own goals and steps end-to-end, with post-hoc audit.

Human determinismAI autonomy
Private & Confidential — Prepared for ARAG
04
BUILD VS. BUY
We have invested 3 years and 45 engineers to develop LegalFab so you don’t have to.
Kirkland’s $500 Million AI Gambit Requires a Cast of Hundreds*
$500M
Internal AI build
Strategic DimensionLegalFab Knowledge FabricGeneric Analytics Platform (e.g., Microsoft Fabric + Fabric IQ)Internal Proprietary Build (e.g., Kirkland & Ellis)
Architectural PatternTrue Data Fabric: Active metadata layer; source data stays entirely in place.Data Lakehouse: Forces physical centralization of all data into OneLake.Custom Monolith: High technical debt; locks teams into a single infrastructure build.
Entity Resolution & ContextPersistent Resolution: Resolves and stores actual cross-source entity instances natively.Definitions Only: Fabric IQ tracks type definitions, not resolved instances; requires 3rd party add-ons.Manual Code: Must build complex identity matching and legal ontology from zero.
External Intelligence (OSINT)Native Wiring: Real-time sanctions, PEP lists, and corporate registries injected directly into live graph workflows.None Out-of-the-Box: Requires custom ETL pipelines to copy sensitive regulatory data into a vendor lake.High Maintenance: Requires manual creation and ongoing SLA tracking for hundreds of custom APIs.
Time-to-Value & Total CostDeployed in Weeks: Shipped as a productized, SOC 2 Type II compliant stack leveraging 200+ pre-built MCP connectors.Months to Years: Requires massive model rebuilding, custom configurations, and deep Microsoft stack lock-in. Labor & resource-intensive ETL.6 Years & $500 Million: Budgeted internal baseline required by firms like Kirkland & Ellis to attempt equivalent capabilities. Labor & resource-intensive ETL.
On average, best of breed implementations take 28 – 48 months and cost €35M to €45M.
Private & Confidential — Prepared for ARAG
05
MATURITY
Technical & Organizational Maturity

Audited Rigor

Robust Compliance Alignment: Structured on annual penetration audits, aligned directly with UK GDPR DPA, Cyber Essentials Plus, SOC II Type II certified and ISO 27001 standards.

Big 4ADOPTED
Adopted by one of the Big 4
SOC 2TYPE II
SOC II Type II Certified
ISO27001
ISO 27001 Standards
CE+CYBER
Cyber Essentials Plus
GDPRUK DPA
UK GDPR DPA Aligned
Private & Confidential — Prepared for ARAG
06
ENABLEMENT PLATFORM
Delivering a Future Enablement Platform
INITIATIONPHASE 1PHASE 2
DISCOVERY
Define Vision and strategic use cases
PLANNING
Shape use case and project infrastructure
IMPLEMENTATION
Sprint cycles
ROLLOUT
Deploy final solution and start operations
GovernanceProject ManagementDefine use case and break down to stories, features and epicsDefine project gov. and teams, derive and refine project backlogManage the Project (Build Charter and Work Plan; Define and Manage Team; Manage Scope, Risks, Actions, Issues, and Decisions)Ensure operational handover
Transformation RoadmapDevelop knowledge vision and derive resulting transformation approachCreate transformation backlog incl. business case preparationFinalize measurable success criteria and prioritize deliverables · Define implementation approachStart new use case (Design phase) for the next phase
BusinessOrganizational ChangeIdentify impact on roles and organizational structuresIdentify changes to client organization, skills and staffing · Implement new/changed R&RAdopt AI-learnings and shape future of workingOnboard people to their new ‘reality’
Process designIdentify process landscape and impacted processesDesign future business processesImplement new business processesContinuously refine configurations and policies
Data and PoliciesIdentify in scope metadataAutomated domain and schemas discovery and confirmationConfigure ontologies and schemas · Configure policies · Review / enhance / manipulate data prior to deploymentContinuously refine configurations and policies
TechnologySystem DeliveryUnderstand client IT landscape and Gap-analysis to specified requirementsInstall the systemConfigure the system · Build agentic assets · Enhance / manipulate data prior to deploymentDeploy the system
Internal/External systems IntegrationIdentify sources and understand integration requirementsDevelop integration strategy and planCalibrate and adjust data sources and MCP connectors · Connect relevant internal and external data sourcesDeploy the system
Architecture and InfrastructureUnderstand architecture and Infrastructure StrategyPlan / design architecture and infrastructureProvide / prepare target infrastructure · Manage infrastructure and environment needsDeploy the system
TestingIdentify success criteriaDevelop test strategy and planConfiguration design Review · Execute testing planPerform UAT and achieve final client approval
PeopleChange ManagementDevelop Change Management strategy and planOnboard Business and IT stakeholdersAssess organizational change readiness · Execute change management plan, ensure leadership alignment and stakeholder engagementOnboard people to their new ‘reality’
TrainingDefine success criteriaAccelerate future skill sets and develop training strategy / planDevelop learning journey and prepare TTT approach · Deliver trainingConduct End-User training and operational hand over
RiskRegulatory ComplianceIdentify compliance areas of interestDerive and assess regulatory compliance requirementsConfirm regulatory compliance is metConduct assurance reviews
Security and ControlsIdentify client security and cyber strategiesConduct threat risk assessmentConduct security testing, penetration testingConduct assurance reviews
Cloud StrategyIdentify client cloud strategyPlan / design cloud roadmapProcure / prepare cloud infrastructure · Manage infrastructure and environment deploymentConduct assurance reviews
LegalFabClientBoth
Private & Confidential — Prepared for ARAG
08
ROADMAP TO VALUE
Roadmap to Value
Pre-engagement
Month 1
Month 2
Month 3
Month 4
Month 5
Contractual
Agree Contact
EXECUTE CONTRACT
Discovery & Planning
UC1 D&P workshops
D&P finalization
UC2 D&P workshops
Implementation
Installation & Configuration
KF Implementation
Utility Implementation
Integrations
MCP Building and Connecting
Acceptance
KF Acceptance
Utility Acceptance
Rollout
GO LIVE 1
GO LIVE 2
Governance
MilestoneWeekly sessionMonthly session
Private & Confidential — Prepared for ARAG
09
IMPLEMENTATION
Expanding Implementation Approach

Transformation path

The below represent an example of an approach to commence with the implementation of a core utility and expand the program swiftly to additional capabilities and business areas

INITIATION
Phase 1
Phase 2
Phase …
Phase n
Implemented Agentic Utilities
PRICING
MARKET INTELLIGENCE
COMPLIANCE
A
B
C
D
Impacted Business Units →
Domain Discovery
Knowledge Fabric
Transformation path — increasing value
Comments
  • Starting with domain discovery and prioritizing the operational systems to connect into the Knowledge Fabric systematic expansion with measurable impact
  • Managing the speed of change through sStep-by-step introduction Further use cases in the organization
  • After the baseline has been established, a further use case will be
  • Accelerated identification and implementation (agile sprints)
  • Significant Cost reduction with each stage of expansion (Decreasing marginal costs)
Private & Confidential — Prepared for ARAG
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