The configurable AI-brain platform

Build an AI agent for any domain — by configuring it, not coding it.

PrepMind is one engine you aim at any use case. Define a persona, connect your knowledge, choose the actions and guardrails, then publish a voice-and-text agent through a deterministic gate. No prompt-wrangling, no glue code — just typed choices.

Launch Studio See how it works

Voice + text, real-time
Knowledge-grounded
Deterministic policy gate

One platform, many use cases

The same engine, pointed anywhere you need it

PrepMind has no built-in domain. A semantic firewall keeps the core meaning-free, so a single engine could be configured for any of these. The examples below are illustrations of reach, not a catalog of shipped products — the only thing that changes is the configuration.

Customer support

Resolve tickets over chat and voice, grounded in your help center and policies.

support.example

Coaching

Guided, persona-driven sessions that adapt to each person's goals and history.

coaching.example

Interviewing

Structured, fair conversations with scoped follow-ups and recorded rationale.

interviewing.example

Sales & outreach

Qualify, recommend, and follow up with guardrailed, on-brand messaging.

outreach.example

Research assistants

Synthesize from your sources with citations and permission-filtered retrieval.

research.example

Tutoring

Patient, level-appropriate teaching that stays inside your approved curriculum.

tutoring.example

Internal automation

Drive internal workflows and approvals through governed, auditable actions.

internal-ops.example

…and your domain

Anything conversational. If you can configure it, the engine can run it.

your-config.example

Domain-neutral by architecture. Meaning is assigned only by your configuration — never baked into the engine.

Why PrepMind

A platform for building agents, not a single bot

Every capability is a typed choice in the Studio — composable, inspectable, and governed.

Configure, don't code

Build through a Studio of typed screens — persona, knowledge, actions, policies, outputs. No prompt-wrangling and no glue code to maintain.

One engine, any domain

A semantic firewall keeps the core use-case-agnostic. Point the same engine at support, tutoring, or internal ops purely through configuration.

Voice + text, real-time

Ship streaming conversational agents — not just a chat box. The same configuration drives both spoken and typed interactions.

Knowledge-grounded

Bring your own sources. Retrieval is permission-filtered and fail-closed, so answers stay inside what each audience is allowed to see.

Governed by a deterministic gate

Models propose; a deterministic Policy Gate decides. You get approvals, a full audit trail, and guardrails that behave the same way every time.

Simulate, publish, roll back

Test a config before it ships, publish immutable versions, and roll back instantly — then watch every live decision get traced and costed.

How it works

Configure → Simulate → Publish → Monitor

A single, repeatable loop takes a config from idea to live agent — and keeps you in control after it ships.

Configure

Set persona, knowledge, allowed actions, guardrail policies, and audience-scoped outputs in typed Studio screens.

Simulate

Run the config against real scenarios. Inspect retrieval, gate decisions, latency, and cost before anyone is on the other end.

Publish

Promote through the deterministic gate as an immutable version. Roll back to any prior version instantly if you need to.

Monitor

Watch it run live with a full audit feed — every decision traced and costed, with approvals where you want them.

The semantic firewall

Trust comes from the architecture, not a setting you forgot to flip

PrepMind separates the meaning-free engine from your domain meaning, and puts a deterministic gate between what the model proposes and what your users ever see.

Meaning lives in your config — the core stays domain-neutral, so nothing is hardcoded to one vertical.
Models propose, the gate disposes — guardrails are deterministic and behave identically every run.
Fail-closed retrieval — answers are permission-filtered to what each audience is allowed to see.
Immutable, auditable versions — one gated intent fans out to many audience-scoped projections, all traced.

Configure your first agent today

Open the Studio, set your typed choices, and simulate a voice-and-text agent before you publish — no build step, no boilerplate.

Launch Studio See how it works

Early platform · build by configuration, not code