Evidence Verification
Outputs are grounded with traceable evidence when facts matter—no blind guessing.
New category: Trusted Action Model
AI that doesn’t just generate — it acts safely, and proves it.
DSONAI turns intent into execution with evidence verification, risk + policy gating, human verification (2FA) for high‑risk actions, and audit‑grade proof for every outcome.
Verified
Evidence‑linked outputs
Governed
Policy + risk approvals
Audited
Proof of every action
DSONAI Console
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This action is classified as High Risk. Please complete Human Verification (2FA) to proceed. If you cannot complete 2FA, the system will mark this action as AI‑initiated and block execution.
What DSONAI delivers
A production‑ready execution layer for AI—built for trust, governance, and enterprise control.
Intent + Risk Engine
Every request is classified by intent and risk tier (Low/Medium/High) before any action runs.
Policy + Approvals
Rules decide what is allowed, what needs approval, and what requires real‑human verification.
Human Verification (2FA)
High‑risk actions are blocked unless the real human completes 2FA—AI cannot impersonate approval.
Audit‑Grade Proof
Every action produces a complete record: intent, evidence, policy decision, approvals, and execution steps.
Privacy‑First Personalization
Preferences and memory are controlled, revocable, and isolated—designed for trust and compliance.
How it works
A simple pipeline that turns user intent into safe, verifiable execution.
Build
Code
Test
Deploy
Monitor
Rollback
AI executes end‑to‑end software delivery like an always‑on engineering org — with safety gates and proof.
With DSONAI, every step is evidence‑verified, classifies intent + risk, enforces policy, and for high‑risk actions requires real human 2FA / approval — then produces audit‑grade proof of what happened.
Result Enterprises finally get large‑scale automation without fraud, compliance risk, or runaway autonomy.
The 5‑step pipeline behind every action
1
Connect toolchain
Source control, CI/CD runners, cloud accounts, observability, ticketing. Least‑privilege scoped credentials per environment.
2
Understand intent
Classify what the user is trying to do and assign a risk level.
3
Verify evidence
Fetch supporting context and attach traceable evidence to factual outputs.
4
Enforce policy
Apply org rules: allow, require approval, or require real‑human verification (2FA).
5
Execute + prove
Run the action and store proof: what happened, why, and who approved it.
Human vs AI clarity
High‑risk actions require human verification. If challenged, the system can disclose that it cannot complete 2FA—preventing impersonation by design.
Why enterprises adopt DSONAI
Because autonomous action without governance becomes fraud, compliance risk, and operational chaos.
Security & Compliance
- Risk‑based gating with approvals and human 2FA
- Immutable audit trails for every action
- Least‑privilege integrations + scoped permissions
- Policy enforcement across tools and workflows
Operations & Productivity
- Safe automation for routine execution
- Fewer errors through evidence verification
- Faster cycle times: email, tickets, approvals
- Clear accountability: who approved what and why
Governance for Agentic AI
- Standard interface for AI execution across systems
- Human vs AI proof stamps for sensitive actions
- Continuous monitoring and policy updates
- Designed for enterprise rollout and control
Roadmap
A focused path from MVP to production adoption.
MVP
Core orchestration • intent+risk • 2FA gates • audit log • email/chat/calendar
V1
Evidence verification • policy admin console • reliability harness • pilots → paid
Scale
More integrations • role-based policies • compliance readiness • enterprise rollout
Contact
Host this page, start collecting interest, and book demos.