Run your company
as a closed loop.
Open-loop companies leak value at every handoff.
AI-native ones close the loop on every signal that matters.
Toposi is how you build the second kind.
The thesis
AI-enabled is not the same as AI-native.
AI-enabled companies bolt copilots onto existing workflows. The work still routes through the same human bottlenecks, the same unread emails, the same dashboards nobody opens. Productivity goes up; structure stays the same.
AI-native companies treat AI as the operating system. Every signal is a trigger. Every decision is logged. Every artifact is queryable. Middle layers of routing collapse. Outcomes feed the next decision automatically.
That structure has a shape — a closed loop. Toposi is the platform for building it.
Open loops bleed. Closed loops compound.
The same operation, two architectures. One loses context at every step. The other learns from every cycle.
Open-loop
The default state of most teams.
- • Signals arrive in DMs, emails, dashboards — and most never reach the right person.
- • Decisions get made and rarely measured.
- • Knowledge lives in heads, Slack threads, and the wrong Notion doc.
- • "What changed last week?" requires a meeting.
- • Improvements depend on someone remembering to retro.
Closed-loop
The default state on Toposi.
- • Every signal is a trigger. The loop runs without anyone routing it.
- • Every decision and outcome is persisted to the project memory.
- • The organization is queryable — in plain language or SQL.
- • "What changed last week?" is a question, not a project.
- • The loop refines itself from its own outcomes.
The five steps of every loop.
Sense, Decide, Act, Learn, Govern. Toposi ships every primitive each step needs.
Sense
Inbound email, webhooks, schedules, the chat widget, voice calls, and 1000+ integration triggers all wake an agent the second a signal lands.
Decide
Each project carries its own memory — DB and filesystem. Every agent reads the project's history, the relevant playbook, and current context before it picks a move.
Act
1000+ tools via Composio, real browsers when there is no API, sandboxed code, structured artifacts, and outbound on every channel — voice, email, chat, and integrations.
Learn
Every run is an artifact. Tool calls, decisions, outcomes, and side-effects are persisted. The project DB is queryable by the next run — the loop's outcomes become its inputs.
Govern
Permissions are explicit per agent. Sensitive actions gate on human approval. The org-wide Sentinel watches every run. Audit, rate limits, and policy memory are all built in.
Built for closed-loop ops.
Eight primitives that turn signals into self-improving systems.
Agents with identity
Every loop has a named owner. Agents have purpose, permissions, and an email address — so escalations, replies, and audit trails always trace back to a known actor.
Memory you can query
Every project owns a Postgres database and a filesystem. Agents read it, write it, and you can SQL it. The org becomes queryable instead of buried in DMs.
Triggers everywhere
Cron, webhooks, inbound email, agent-to-agent delegation, the chat widget, and voice calls. Any signal in your business can wake the loop.
Sandboxed execution
Each run gets an isolated environment. Generate reports, run code, fan out to systems, hit real browsers — without touching your production infrastructure.
Permissioned and audited
Granular per-agent permissions, explicit human-in-the-loop on risky actions, full audit log, and an org-wide Sentinel that monitors every run.
Email is a first-class channel
Every agent gets an email address. Hand off, delegate, or just reply — the loop closes through the channel humans already live in.
Structured artifacts
Reports, dashboards, briefs, and structured outputs aren't a side-effect — they're a deliverable the next run can read.
Multi-agent by design
Agents delegate to peers. Teams share projects. The Sentinel watches the org. You get a fleet, not a single bot.
Govern — the fifth step
Autonomy is only useful if you can trust it.
Toposi doesn't bolt on governance — it's a step in every loop. Permissions, approvals, scope, and audit are first-class primitives, not afterthoughts.
Per-agent permissions
14 capability flags — read files, query DB, write DB, browse web, execute code, notify, and more. Nothing is on by default. You opt in to each one.
Human-in-the-loop
Mark sensitive actions for approval. Agents pause, email the right human, and resume on a one-click yes. Decisions can be saved as standing policy memory.
Scope boundaries
Restrict which inboxes, paths, integrations, and data sources an agent can touch. The agent only sees what its job requires.
Sentinel + audit log
Every tool call, every decision, every artifact is recorded. The org-wide Sentinel watches every run for policy drift, runaway spend, and unsafe moves.
Why this is different.
Most "AI tools" inherit your full account on day one — your inbox, your CRM, your files, all of it. Toposi agents start with zero capabilities. Each one is granted the minimum it needs, supervised at the edges that matter, and watched org-wide by the Sentinel. You scale autonomy by policy, not by hope.
See the full guardrailsA principle
Loops are the unit of work.
AI-native companies don't draw process diagrams — they spin up loops. Toposi is built so each loop senses, reasons, acts, reports, and learns on its own, without negotiating with a queue. You add capacity by adding loops, not by hiring routers and reconcilers.
Six loops, ready to run.
Each loop is a closed-loop pattern with five steps mapped to real tools. Pick one and the first cycle runs the same day.
Go-to-market
Customer
Close your first loop.
Pick a blueprint, connect your tools, and watch a real cycle run end-to-end. Free to start.