Prodis.ai
Coming soon
For teams shipping AI safely

Backend-verified AI for production APIs

Generic chatbots let the model run the loop. Prodis lets the model interpret intent while your backend verifies plans, access, evidence, computation, and answer readiness.

One-afternoon integration

A working assistant quickly. Correctness controls from day one.

Add the open-source host adapter, point Prodis at your existing API, and get a usable assistant without rewriting your service around an AI framework.

A Prodis assistant does not answer just because the model sounds confident. It answers when the runtime has verified the question, plan, permissions, evidence, computation, and final answer readiness.

30-minute first integration Backend-verified answers Fail-closed runtime Evidence contracts No API rewrite Auditable run trail
Runtime contrast

The model proposes. The backend verifies.

The important difference is not whether an assistant can call tools. It is who owns control when production data, permissions, and answer correctness are on the line.

Generic chatbot loop
  1. User asks a business question.
  2. The model chooses tools and parameters.
  3. API data returns to the model.
  4. The model decides if it has enough.
  5. The model writes the final answer.
Prodis verified runtime
  1. The model interprets user intent.
  2. The backend validates the plan.
  3. API access runs through host permissions.
  4. Evidence contracts check readiness.
  5. Computation and synthesis happen only when verified.

The difference is control. In a chatbot loop, the model owns too much of the runtime. In Prodis, the model proposes and the backend verifies.

Production trust

Built for teams that cannot afford confident wrong answers.

Production assistants need more than fluent responses. They need access control, traceable evidence, deterministic computation, and clear refusal paths when the data is missing, ambiguous, or unauthorized.

Wrong-answer risk

Evidence contracts make answer readiness explicit before final synthesis.

Access risk

API execution stays behind your application's existing authentication and permissions.

Audit risk

Every answer has a trail: plan, endpoint calls, evidence, computation, and synthesis.

Operational risk

The assistant fails closed when the request cannot be safely answered.

Core capabilities

The control plane behind reliable API-facing assistants

High-leverage primitives for teams building customer-facing and operator-facing assistants over production APIs.

01

Framework-native API introspection

Understand live APIs through framework adapters instead of brittle manual prompt inventories.

02

Typed endpoint contracts

Capture request and response semantics in machine-usable contracts the planner can trust.

03

Validated planning

Reject invalid or unsupported plans before execution instead of repairing bad tool calls after the fact.

04

Evidence sufficiency

Make answer readiness explicit so the system knows when evidence is complete and when it is not.

05

Deterministic derivation

Use controlled computation for rankings, grouping, and synthesis over API data instead of prompt-side guesswork.

06

Safe customer/admin-facing answers

Support reliable answers across customer and operator contexts without collapsing correctness into style.

07

Hosted control plane

Centralize contracts, runs, evidence, and policy in one service while keeping host APIs first-class.

08

Step-by-step auditability

Trace every answer at the most granular level so teams can spot mistakes, inspect derivation, and debug with confidence.

Early access

Get the first preview.

Join the private waitlist for early product updates and launch access.

waitlist@prodis.ai