Executive Summary

Companies that deploy cloud-hosted AI assistants face real exposure of sensitive IP and regulated data to third-party processors, a problem that primarily burdens compliance, security, legal, and IT teams at mid-market and enterprise firms. There are roughly 200,000 such organizations in scope, yielding an addressable market of about $12.0B (200,000 × $60K ACV), and analysts score this opportunity 88/100 for market attractiveness. You could build a vendor-agnostic registry and orchestration layer that lets organizations register data stores, on‑prem or private cloud GPUs, and policy rules so assistant tasks are executed locally or within approved environments; core features would include connectors, a policy engine, routing, audit logs, and runtime adapters to popular open LLMs and inference stacks. The product should expose developer-friendly SDKs and admin UIs to enforce data residency, RBAC, and tamper‑evident auditing so legal and security teams can certify deployments. The timing is favorable: regulatory scrutiny around data residency is rising, and efficient open LLMs plus optimized runtimes have materially reduced the cost of local inference, making private assistants technically and economically viable. Enterprises are actively looking for vendor-agnostic orchestration to avoid lock-in, and with a conservative $60K ACV the revenue potential merits serious investment (revenue potential scored 82/100), even accounting for longer sales cycles. To differentiate, prioritize hardened compliance primitives (SOC2/ISO-ready controls), out-of-the-box connectors for ERP/CRM/document stores, and operational tooling that minimizes the maintenance burden of on‑prem inference while providing clear TCO comparisons versus cloud alternatives. Be honest about challenges: competition is medium (cloud vendors and specialized vendors), enterprise sales cycles and integration work are lengthy, and you will need to invest upfront in security certifications and deep integrations before trust—and revenue—will materialize.

Market Opportunity

Keep AI assistants local by registering company resources for private tasking targets a $12.0B = 200,000 mid-market & enterprise customers × $60K ACV total addressable market with medium saturation and a year-over-year growth rate of 22% YoY (IDC & McKinsey estimates for enterprise AI/ML and private model adoption).

Key trends driving demand: Regulatory and compliance scrutiny around data residency is increasing — this creates demand for on-prem or private processing options.; Open and efficient LLMs plus optimized runtime stacks are reducing the cost of local inference — this makes private assistants technically and economically viable.; Enterprises prefer vendor-agnostic tooling that can orchestrate multi-cloud and on-prem resources — orchestration layers that streamline that complexity are becoming strategic.; Security teams are adding data-exfiltration controls to procurement checklists — products that provide verifiable attestation and policy controls have a procurement advantage..

Key competitors include Microsoft Copilot, Hugging Face (Inference + Private Hosting), MosaicML / Private Model Providers.

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Keep AI assistants local by registering company resources for private tasking

Executive Summary

Market Validation

Market Opportunity

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