Take your end-user communication to the next level with AI
Tailored AI solutions to enhance customer engagement and streamline operations
A cutting-edge framework based on state graphs
What is ExoChat?
ExoChat is an M2P (Machine-to-Person) engine for designing and executing managed, stateful LLM dialogues. It turns prompt chaos into a state-and-transition architecture, delivering deterministic behavior, testability, and scalable scenarios without involving developers in every change.
State graphs
Scenarios are defined as finite-state graphs with clear goals, data, and transition rules per state.
Prompt control
Context assembly from facts, history, and policies with model routing for classification, generation, and verification.
No-code iteration
Operators and analysts change behavior visually and ship versions with A/B and feature flags.
Advantages
- Development Speed — reduces time from idea to launch.
- Quality Control — built-in checks and validation of AI responses.
- Flexibility — adapts to industries and tasks.
- Data Extraction — collects structured facts during dialogues.
- Integration — ready for leading LLM providers.
- User-friendly interface — intuitive for non-technical users.
Key idea: M2P instead of H2M
Traditional H2M (Human-to-Machine) prompts let humans steer the model. ExoChat implements M2P: the machine guides the person through predefined logic and goals while respecting domain rules and business constraints.
How it works
- Initiation: event or request comes from UI or integration.
- State selection: load active state, rules, facts, and policies.
- Prompt formation: assemble context and choose the model.
- LLM call: execute, then validate, normalize, and filter.
- Transition decision: check conditions, persist facts, and move to the next state.
- Observability: log artifacts and metrics for QA and audit.
For product teams
Multimodel orchestration
Route requests across providers by quality, cost, or latency policies.
Facts & artifacts
Store confirmed statements (e.g., consents) and dialogue data in a structured form.
Testing & debugging
Branch runs, scenario inspection, regression suites, and observability at each step.
Security & compliance
- PII masking in logs and configurable retention policies.
- Scenario versioning and artifacts for auditability.
- Roles and permissions for operators, analysts, and developers.
- Policies for model routing, fallback, and guardrails.
Our projects
Stamina
AI-based psychologist helping people overcome anxiety, depression, and addiction. Empathetic conversations powered by GPT to support individuals and bridge access gaps.
Frequently asked questions
How does the system help create chatbot behavior scenarios?
By modeling dialogues as state graphs with clear goals, rules, and transitions, plus visual editing and testing.
Can I visualize the chatbot’s behavior flow?
Yes. Scenarios are visualized and can be edited without code, with instant debugging and previews.
Can the system handle complex multi-step conversations?
Yes. ExoChat supports multi-step, branching dialogues with validation, facts storage, and deterministic transitions.
Is the system suitable for non-technical users?
Yes. Operators and analysts can design, test, and ship updates without developer involvement.
How does the system ensure accessibility for all users?
By providing structure, validation, and consistent patterns that keep interactions focused and easy to follow.