Sophona is an agentic automation platform built around a Skill Map graph. The graph dynamically gates context so the agent has access only to skills relevant to the current business path — instead of a flat prompt stuffed with every tool. Each skill is a self-contained workflow runtime that can call AI in real time (planning, tool routing, retries) and apply Mind Inject procedures at the right moment, giving you full control over how the agent behaves without hardcoded logic.
The same agent operates through phone, embedded web widget, desktop widget, and API/iPaaS — one runtime, multiple interfaces.
Instead of a flat list of tools, Sophona uses a skill graph. At any moment the agent sees only skills relevant to the current business path — reducing context and improving reliability.
Every skill is an executable workflow that can call AI in real time (planning, tool routing, retries) and apply Mind Inject inside the skill — not only at the top-level agent.
You can inject procedures and policies at runtime — globally, per business path, or per skill. This enables deterministic, auditable behavior without hardcoding logic.
Skills can execute real work: clicking, navigation, form filling, desktop operations, and API calls — verified and repeatable.
Pro (Founders/Business) instances run in isolated single-tenant mode: separated runtime, data boundaries, and per-tenant configuration — built for enterprise expectations.
The Skill Map selects the relevant branch (context gating). Then the chosen skill runs as an independent workflow that can plan, call tools, inject procedures, and verify outcomes. This makes behavior flexible, testable, and business-controlled.
A trigger comes from phone / widget / desktop / API. The Skill Map graph activates only the subset of skills relevant to the current business path, optimizing context and reducing noise.
The selected skill runs as its own workflow and can call AI live for planning, routing, retries, and tool usage — without bloating the global prompt.
Procedures can be injected globally, per path, or per skill. This provides predictable execution and full business control — without hardcoded decision logic.
In Sophona, a skill can be tiny (like a single UI click) or a full, structured workflow with variables, conditions, retries and verification. This lets you choose between autonomy and determinism — without hardcoding agent logic. You control behavior by designing the skill graph.
You can give the agent atomic skills like Click, Input, Wait, Read UI. Then the agent autonomously tries to complete the process by selecting and chaining these skills (guided by the Skill Map graph and Mind Inject).
Or you can build a classic workflow skill: variables, conditions, timeouts, retries, and verification. AI is called only where it adds value (interpretation, routing, drafting) — while the core execution stays deterministic.
Reliability comes from structure: verification steps, evidence collection, and limiting AI to controlled surfaces. If you want 100% stable behavior, you can keep skills fully deterministic and use Mind Inject to enforce procedures.