Give your AI Agents hands
that don't slip.
Stop letting your agents "guess" their way through messy UIs. Verity provides the Deterministic Execution Layer that makes AI automation 100% reliable—even on legacy apps without APIs.
Most automation tools are good at demos and weak at execution
Current AI Agent Way
AI Agents are probabilistic—they hallucinate, time out, and lack the precision for mission-critical tasks.
Traditional RPA Way
Built on brittle DOM selectors that break the moment a browser updates.
The Verity Way
A deterministic execution backend for web operations, with verification, retry safety, and explicit failure handling built in.
A backend for reliable execution
Intent becomes a canonical action
Verity translates a requested task into a structured action contract with typed inputs, expected outcomes, and verification requirements.
Execution uses the best available path
Verity prefers APIs first. When APIs are unavailable, it can fall back to a Shadow Map execution spec for controlled UI-based execution.
Success is verified, not assumed
Every action defines the observed state that proves it succeeded. Evidence, logs, and result shape are part of the product contract.
Retries stay safe
Idempotency and failure classification are built into the execution model so partial failures can be recovered without guessing what already happened.
What makes Verity different
Deterministic by design
Verity is built around verified state change, not best-effort task completion.
Schema-first execution
Actions, verification, evidence, and failure handling are explicit contracts instead of connector-specific glue code.
API-first, UI fallback
Use stable system interfaces when available, and fall back to structured browser execution only when necessary.
Observable from the start
Logs, evidence, and execution status are first-class so operators can understand what happened and why.
Safe under retries
Verity is designed for real operational environments where timeouts, partial writes, and retries are normal.
| Feature | Legacy RPA | Gen-AI Agents | Verity |
|---|---|---|---|
| Logic | Static / Rigid | Probabilistic | Deterministic |
| Maintenance | High (Selector Drift) | Variable (Prompt Drift) | Near Zero |
| Legacy Support | Poor (Brittle) | Non-existent | Native (ShadowMap) |
| Trust Layer | None | Low (Black Box) | High (Audit-Ready) |
Where Verity fits first
Cross-system operational workflows
Run workflows that need to coordinate actions across internal systems, SaaS tools, and web interfaces with explicit verification at each step.
Back-office reliability layers
Add a correctness and retry-safe execution layer underneath agentic or rules-based systems without trusting them to act directly.
Long-tail SaaS operations
Handle important actions in systems that do not expose clean APIs by using structured UI execution with verification instead of brittle scripts.
Operational state changes that matter
Notifications, ticket updates, contact creation, inventory actions, shipment tracking, and similar workflows where correctness matters more than raw speed.
Built around execution guarantees
Verity is organized around a canonical contract for actions, connectors, verification, evidence, and failure handling. The current product foundation includes reusable schemas, deterministic workflow execution, connector adapters, and a Shadow Map spec for UI-based fallback execution.
This is not an agent wrapper and not another orchestration layer that stops at "task attempted." Verity is designed to become the execution foundation underneath higher-level systems that still need correctness guarantees.
Early Access
We're looking for teams with operational workflows that are too important for brittle automation and too messy for API-only tooling. If that sounds like you, we'd love to learn what you're running into.
Frequently Asked Questions
Everything you need to know about deterministic execution vs probabilistic AI.