Prodis Technologies, Inc. · Memo № 001 · Rev 2026.05.01 · Doc 001-A · Page 01 / 01
From Prodis Engineering
To Teams shipping AI over production APIs
Re A working method for AI answers your backend can stand behind
Keywords no API rewrites · backend-owned runtime · typed endpoint contracts · evidence contracts · deterministic derivation · step-by-step auditability

The model proposes.
The backend executes.

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 correctness. The model is one component. The backend owns control.

§ 01

Premise.

Production assistants cannot afford confident wrong answers.

Production assistants need more than fluent responses. They need access control¹, evidence-checked answers², audit-traceable steps³, and a clear refusal path⁴ when data is missing, ambiguous, or unauthorized. Polished language is not correctness.

§ 02

Control.

The model proposes. The backend executes.

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.

Fig. 01 — Loop vs. Runtime Drawn 2026.05.01
Chatbot Loop
  1. 01user asks
  2. 02model picks tools
  3. 03api returns data
  4. 04model decides if enough
  5. 05model writes answer
answer
Prodis Verified Runtime
  1. 01model interprets intent
  2. 02backend validates plan
  3. 03authorized APIs execute
  4. 04evidence is assembled
  5. 05result is derived
answer (only when verified)
The difference is control. In a chatbot loop, the model owns too many decisions. In Prodis, the model proposes and the backend executes.
§ 03

Integration.

30 min

A working assistant in 30 minutes.
Correctness controls from day one.

Works with your APIs out of the box, no rewrites. Install the Prodis adapter or plugin and get a usable assistant without rebuilding your service around an AI framework.

§ 04

Apparatus.

The verification layer behind reliable API-facing assistants.

Capabilities for teams building customer-facing and operator-facing assistants over production APIs.

  1. 01

    Framework-native API introspection

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

  2. 02

    Typed endpoint contracts

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

  3. 03

    Validated planning

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

  4. 04

    Evidence sufficiency

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

  5. 05

    Deterministic derivation

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

  6. 06

    Safe customer and operator answers

    Support reliable answers across customer and operator contexts without treating polished language as correctness.

  7. 07

    Hosted control plane

    Manage contracts, runs, evidence, and policy in one hosted service while your APIs remain the source of truth.

  8. 08

    Step-by-step auditability

    Inspect each step so teams can spot mistakes, review derivation, and debug with confidence.

§ 05

RSVP.

Early preview by request.

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

RSVP → waitlist@prodis.ai