◉ how our platform solves this · finance/markets
find the signal. we run the math.
The work is the point — but the desk drags behind every piece of it: the prep, the formatting, the checks before anything goes out, the same steps run again and again. It’s the work around the work, and it never finishes.
◉ the answer
Agentic workflows run reconcile → check → report on your own infrastructure — against your own models — with a human on the gate for anything that acts, and the record written as it goes.
◉ how we solve it · our process
- Chat — you state the goal in plain language; we shape the work with you.
- Flows — it becomes a repeatable workflow, on rails and fully auditable.
- Missions & Fleets — coordinated across as many instances as the job needs.
- Synth · Brainbow · Code Mode · Exec — the right tool spun up for each step: a throwaway utility, a driven browser, code run against your real systems.
- your ground, your gate — every step on your infrastructure, a human approving anything that acts.
◉ the mechanism · what actually happens
One request, walked end to end — every step on your infrastructure, against your own models, with a human on the gate.
- ChatMode
You state the goal in plain language — “reconcile the book, check the limits, draft the report.” ChatMode plans the work and dispatches its built-in agents — planning, data-query, validation, synthesis — to decompose it into pull, analyze, act, assemble. No prompt engineering, no scripts.
- SmartModelRouter
Each step is routed to a model that fits it — a fast model to parse a tick or trade feed, a long-context model to read a long research note or filing, a strong reasoner to judge a reconciliation break or a risk limit — across the providers you register. Bring your own models and run them on your own infrastructure; your positions, your book, and your client data stays inside your network.
- MCP tools · OBO credentials
Agents reach your market-data feeds, OMS, books and records, and your risk system as MCP tools, each call running under your own identity. The platform forwards your scoped credentials per call — no shared token, no pooled service account, no secret pasted into a prompt. Every call is logged.
- Tool Synthesis · Code Execution
Sources never agree on format. Code Execution writes a one-shot Python tool on the fly to write a one-shot reconciliation or pricing tool, run it sandboxed, and discard it — credentials injected at runtime, run in a hardened sandbox, then discarded. No tool is registered, nothing persists.
- AgenticWorkflows
The reconcile → check → report flow becomes a flow of named agents — repeatable, auditable, on rails. And there’s more behind sign-up: pre-trade compliance checks, end-of-day reconciliation, and the regulatory-reporting prep — the many ways the platform runs this, with more revealed after you sign in.
- HITL approval
Nothing acts until you say so. The human-in-the-loop gate is real architecture, not a setting — any step that would place an order or post to the book stops and waits for a person; if no one approves, it times out and is denied. You review the plan and the scope, and approve before anything happens.
- Tool synthesis · the recurring work, off your plate
The repetitive research toil — cleaning a dataset, reshaping a backtest input, normalizing a feed — the platform turns it into a one-shot tool the moment you ask, runs it once with your approval, then throws it away. Nothing persists. You keep your focus on the model and the judgment, not the plumbing around it.
- Audit trail · DLP · RBAC
Every model call, every tool call, every approval is written to an append-only audit log — once a decision is recorded it’s frozen, so the trail is tamper-evident. DLP keeps sensitive material inside your network, and role-based access scopes who can do what. It’s a record you can stand behind.
The toil ran itself, it acted only on your nod, and the record is already written — and that’s one flow. Pre-trade compliance checks, end-of-day reconciliation, and the regulatory-reporting prep are waiting behind sign-up.
◉ go deeper
Run it on your own infrastructure — or with us.
Talk to us to see the platform on your stack — governance, fleet, support, and the enterprise capabilities. Or self-host the platform in your own environment and run the whole thing today.
The platform self-hosts in your own environment — chat, flows, and the ops MCPs. Fleet, Mission, CodeMode, governance and support come with the enterprise platform. Designed for FedRAMP-High deployment.