autonomOS
Unified context for the enterprise.

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The Four Forces Holding Enterprise Intelligence Back
Enterprise Information is Fragmented
  • 900+ applications managed by the average enterprise
  • 71% remain disconnected
  • 95% of IT leaders cite integration as the #1 barrier to AI adoption
  • Shadow IT and "agentic sprawl" compound the complexity
M&A Value is Leaking
  • 70% of deals fail to create intended value
  • Only 30% hit synergy targets
  • Post-merger IT integration averages 18–24 months
  • Up to 50% of potential merger value is missed
Multi-Entity Comprehension is Surface-Level
  • Hyperion and OneStream aggregate GL balances only
  • Operational metadata is stripped away
  • Parent entities see numbers, not the underlying operations
Adaptation is Stalled
  • Legacy architecture cannot support agentic AI
  • Organizations constrained by decades-old record-keeping systems
  • Without a context layer, AI agents remain isolated and ineffective
The root cause of these failures is the same: The Context Gap. Solving this doesn't require a multi-year migration; it requires a lightweight layer that understands what is already there.

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Three Products, One Scalable Platform, Deployed in Days
EnterpriseOS
Single-entity comprehension. The full platform for any enterprise with a complex data architecture that needs to generate a consistent, contextual, reliable data pipeline.
Convergence M&A
The M&A Data Platform. Unified reporting across the combined entity, from due diligence to integration and beyond. What-if scenarios on contextually reconciled data. Proforma financials, normalized EBITDA, Quality of Earnings. Customer cross-sell and upsell analytics. Synergy identification, integration planning, overlap identification across any function. Ongoing synergy execution monitoring.
Convergence Multi-entity
Permanent multi-entity operations — health systems, merged banks, defense primes. Unified, contextual reporting with industry-specific semantic libraries. Far beyond the capabilities of GAAP consolidations, gain semantic understanding of your subs' performance, risk profile, and

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autonomOS: One Intelligent, Extensible Platform
AOS is a lightweight, rapidly deployed abstraction layer that floats on top of your IT landscape.
It doesn't move data. It doesn't replace systems.
It just connects to what's already there.
And understands what's already there.
The same pipeline serves every product.

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Why days, not years.
We connect to what's already there.
There is no data migration, no replatforming and no system replacement. AOS floats on top of your existing IT landscape and reads from the systems you already run. The deployment footprint is a connection, not a project.
Discovery is automated, not workshopped.
AOS discovers your systems, maps their connections, and extracts schemas automatically. What used to take a team of consultants months takes the platform hours.
The semantic layer learns.
AOS resolves field-level semantics automatically — heuristic matching in under a second, AI-powered resolution in seconds more. Stakeholders only spend time on the genuinely ambiguous 10%. The other 90% is resolved ahead of time.
AI leads and automates the onboarding process.
Before a stakeholder sits down, embedded AI agent (AOS AI) has already researched the company, run IT discovery, and generated preliminary semantic mappings. 90 minutes replaces months of back-and-forth.

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Embedded AI Customer Success Agent Who Works 24/7.
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What it is.
AOS AI is a persistent AI engagement lead assigned to every customer. It knows what's been discovered, connected, mapped, and changed — across every module. She remembers context across sessions.
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What it does.
Deployment and onboarding. Real-time system, data and process support. Process management - automated discovery, conflict resolution, triage. Tech support: human-supervised system configuration changes and personalization.
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Why it matters.
Compress implementation from months to days via a 60-minute conversation. Always on, always available, knows everything.

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contextOS: The Living Enterprise Ontology
Enterprise architecture has a language problem: systems speak in disparate tables, while AI requires a unified conceptual framework. contextOS bridges this gap — transforming raw data into a single, consistent, verifiable enterprise ontology that evolves automatically.
Beyond Data-Driven
Agentic AI breaks the assumption that humans can manually supply context for every transaction.
Semantic Layer Required
Agents need a knowledge graph encoding business rules, relationships, and authority.
The Living Record
Unlike static docs, contextOS auto-resolves new fields to business meaning and builds relationship graphs continuously.

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autonomOS
Unified enterprise context and comprehension — deployed in days, not years.
The platform is built and running. We're ready for the conversation
Contact Us

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