Inveniam - The Digital Middle Office for Private Assets

The Digital Middle Office for Private Assets

Less searching, more finding

Transforming the way your assets data is credentialed, extracted, structured and delivered. Unlock digital data on demand for owners, managers, administrators and service providers.

Enable your organization with real time access to trusted asset performance data and save both time and money. Avoid inaccurate or discounted valuations due to unstructured and inaccessible data.

learn more

Sal Companieh

Chief Digital & Information Officer

Cushman & Wakefield

Our investment and partnership in Inveniam is part of our continuing Valuations & Advisory Digital Transformation, which will [...] benefit our clients across multiple businesses that depend in different ways on reliable data.

Sameer Nagpal

President & CEO

JK Tech

By integrating with Inveniam's platform, we are enabling AI-driven automation and data integrity at an unprecedented scale, fundamentally transforming how alternative investments are managed and valued.

G42

Strategic Partner

-

Private markets are the world’s largest asset class but remain hindered by inefficiencies and outdated processes. Through our partnership with Inveniam, G42 aims to leverage AI to revolutionize how private assets are valued, managed, and traded.

Allen Weiss

Fmr. Partner

Apollo Capital Management

Inveniam is helping people monetize their assets with tokenization, and Inveniam's software allows businesses to mark to market the real estate assets they already own.

Shari Noonan

Co-Founder and CEO

Rialto Markets

As the foundational architecture for private markets, Inveniam enables companies like Rialto Markets to deliver greater transparency, trust, and real-time data—accelerating capital formation, trading, and global distribution.

Phil Bak

CEO

Armada ETFs

Valuation and liquidity profiles for real estate and other alternative assets have diverged based on their product structures, but we believe convergence is inevitable.

Mike Lempres

Chief Risk and Trust Officer

Inveniam

I’m excited to join Inveniam at this critical inflection point. The company is building foundational infrastructure for the future of private markets.

Daniel Coheur

Co-founder & CCO

Tokeny

Inveniam is building the common data layer for tokenization to enable many ties across the ecosystem to stay connected to token data

Platform Features

Delivering Data + AI + DLT at Enterprise Velocity and Scale

Inveniam.io transforms unstructured data into trusted intelligence for private market assets using blockchain-based, decentralized data infrastructure

Inveniam.io

The data foundation and architecture powering the systematic trading of private market assets in an AI-driven, agentic future.

Powers next-gen data management for Real Estate, Infrastructure, Private Credit and Private Equity
Facilitate price discovery at scale – feed indices and other financial products by asset and geography
Data insights from private assets, combined with correlated macro data, drive alpha
Leveraging AI to create new private markets investment opportunities
AI automates data structuring at scale to power transparent, efficient price discovery.

learn more

The Inveniam Advantage:
Asset Surveillance for an Agentic Future

Inveniam's data management infrastructure sets the foundation for effective AI agent deployment and asset surveillance

Scaling Asset Surveillance

Scales traditionally manual, resource-heavy function
Builds intelligence from documents to portfolios via tiered agents
Higher ROI through automation and insight

AI-Ready Infrastructure

Federated Data Rooms link client documents to structured data templates
Vector search enables AI-powered document understanding
Structured data supports fast, flexible retrieval

Optimized AI Environment

Comprehensive data collection and indexing
Semantic embedding for deeper AI comprehension
Structured tagging improves retrieval and relevance

Workflow-Oriented Coordination

Templates standardize key surveillance processes
Track document states and task completion
Manages task assignment with permission controls
Sends real-time notifications to stakeholders

Document-Level Agents

Index key terms, entities, and document relationships
Automated extraction of user-defined data fields
Combination of machine learning, AI, NLP, and human-in-the-loop
Apply severity ratings and categorize problems by type

Deal-Level Agents

Compare documents to detect inconsistencies and compliance gaps
Track entity relationships across entire deal structures
Store interim results in persistent memory for reasoning and lookup
Generate KYC/AML reports and automate status updates across workflows

Portfolio-Level Agents

Apply deal-level insights across full portfolios
Aggregate results into dashboards for executive view
Detect systemic risks and emerging exposure patterns

Issue Detection Framework

Identifies 10 structured categories of risk, ambiguities, drafting issues, and missing protections
Classifies each issue by severity level from critical to irrelevant
Applies contextual analysis: party role, agreement type, and business impact

Risk Mitigation

Data Quality: Use validation, confidence scoring, and human review for uncertain inputs
Model Reliability: Maintain human oversight and vet prompts to support AI decision-making
Security & Compliance: Enforce audit trails and cryptographic proof with security-first architecture

ROI Advantage

Operational Efficiency: 60–80% reduction in manual effort and 3–5x increase in surveillance frequency
Risk Management: Identify emerging risks earlier and improve consistency across dimensions
Strategic Advantage: Scale AUM with less headcount and boost investor confidence