Confidential AI for proprietary trading and fintech engineering.
Financial institutions and fintech teams build on algorithms, models, and infrastructure that represent competitive advantage. Cloud AI coding tools create unacceptable exposure risk for proprietary trading logic, risk engines, and compliance-critical systems.
Orgn gives finance teams a confidential agentic stack with governed model access, usage visibility, and isolated execution — so engineering moves faster without sending sensitive code to vendor-controlled inference.
SOC 2 — Evidence-ready controls for regulated finance
Last updated: 2026-05-22
Why finance teams need confidential AI.
Conventional cloud AI tools create exposure risk that security, compliance, and procurement teams cannot accept in regulated environments.
Proprietary code is a competitive asset
Trading strategies, pricing models, and risk infrastructure cannot be sent to public AI APIs where retention policies, training pipelines, and subprocessors create exposure risk that security and legal teams will block.
Challenge
Proprietary code is a competitive asset
Model governance is a board-level concern
Finance teams need to control which models run, what data they see, and how inference is logged. Ad-hoc AI tool adoption creates shadow workflows that compliance cannot audit.
Challenge
Model governance is a board-level concern
Usage and cost must be inspectable
Platform, security, and finance teams need shared visibility into AI usage — not opaque per-seat subscriptions where inference costs and data flows are hidden inside vendor dashboards.
Challenge
Usage and cost must be inspectable
The confidential agentic stack for your industry.
Orgn combines a TEE-backed gateway, confidential IDE, agent control plane, attestation, and isolated sandboxes into one stack designed for sensitive engineering.
Governed model gateway for enterprise policy
Gateway routes requests across TEE and zero-data-retention providers with policy controls finance and security teams can inspect — including usage logging and model selection rules.
Confidential development for sensitive codebases
CDE keeps repositories, prompts, and agent actions inside hardware-protected sandboxes. Engineers get AI assistance without exposing proprietary algorithms to unmanaged cloud tools.
Regulated agent workflows with audit trails
Build and deploy agents for compliance, reporting, and internal automation with controlled tool access, policy-aware execution, and evidence attached to every run.
Assurance by design
Orgn is built for teams that need provable isolation — not policy assurances — before AI workloads are approved for production.
Enterprise policy controls on model routing.
Usage and execution mapped to operators.
Your code is never used to train models.
Finance — common questions
Answers for security, procurement, and platform teams evaluating confidential agentic infrastructure.
Ready to evaluate Orgn for finance?
Talk to the Orgn team about confidential deployments for your industry, or explore all use cases and pricing.