Bounded experiments
Define audience, environment, tools, memory and stop conditions before the test begins.
VALIDATION / SYSTEM 03
Test interaction systems before they become production risk.
Test conversational behavior, monetization, incentives and real user reactions before scaling a voice-driven AI product.
THE OPERATING PROBLEM
From model output to dependable behavior.
Voice products fail in the distance between a scripted demo and an unscripted user. People interrupt, ask for exceptions, misunderstand boundaries and reveal edge cases that no static test set predicts.
IronHeart.AI can operate as a controlled sandbox for evaluating dialogue behavior, emotional dynamics, payments, incentives and tool use. Teams preserve transcripts, outcomes and runtime events while keeping the experiment bounded by product policy.
The goal is not to maximize novelty. It is to learn which interactions are useful, where users lose trust and which behaviors must be governed before a larger deployment.
What IronHeart sells
A configurable cognitive runtime—not a one-size-fits-all robot personality. Partners purchase managed Cloud API access or scope edge, offline, private-cloud and OEM production licensing with integration support.
Observable runtime
Capture interaction events, failures, recoveries and outcomes rather than judging only final answers.
Production handoff
Turn validated behaviors into versioned configuration for cloud, edge or private deployment.
THE COMPLETE COGNITIVE LOOP
Six modules.
One interaction state.
A useful embodied system cannot treat voice, memory and action as unrelated calls. IronHeart coordinates the modules around the live person, environment, role and task.
Each module can be configured per robot or product while published versions preserve a reproducible operational state.
01Perception
02Realtime voice
03Persistent memory
04Personality
05Gaze
06Actions
Define
Choose a narrow behavior, audience and measurable operational outcome.
Instrument
Configure event logs, memory scope, safety rules and human escalation.
Observe
Run with real users and review breakdowns, not only successful conversations.
Promote
Publish a governed version or roll back without losing the experiment history.
BUY & DEPLOY
Start with the integration path that fits the product.
Primary buyer: Product, research and innovation teams validating a robot, AI companion, voice agent or conversational business model.
What to measure: Track completion, recovery, policy compliance, user comprehension, escalation quality and healthy return behavior.
Required controls: Versioned prompts, test identities, memory retention, action allowlists, rate limits and audit events.
Cloud API
Prototype and launch with managed realtime runtime services and the published API plans.
Review pricing →Edge & Offline
Scope interaction-critical components for supported device or nearby edge hardware.
Discuss edge deployment →Private Cloud
Run inside customer-controlled infrastructure with an enterprise integration agreement.
Request enterprise scope →| Foundation model for | Social interaction across perception, voice, memory, personality, gaze and actions. |
|---|---|
| Partner retains | Hardware, customer experience, business rules, data policy, safety authority and go-to-market. |
| IronHeart provides | Runtime configuration, cognitive modules, adapter contract, versioned publication and deployment support. |
| Commercial path | Cloud API subscription for evaluation; custom scope for edge, offline, private cloud and OEM production. |
FAQ
Questions before integration.
Is the sandbox a separate consumer product?
No. It is an implementation approach using IronHeart runtime controls and observability.
Can a failed experiment damage the published robot configuration?
Draft and published configurations can remain separate, allowing tests to fail safely.
Can teams compare multiple personalities?
Yes. Versioned personality, voice and memory policies can be evaluated against the same scenario.
BUILD WITH IRONHEART
What should your robot become?
Tell us about the embodiment, use case and deployment constraints. We will map the fastest evaluation path.