oshal is our premier platform: an open-source agent-swarm runtime that accepts work as tickets, routes each phase to a worker bot, and runs those bots against whichever model harness fits the job — on infrastructure the operator owns. Everything below is source you can read or a system you can open in a browser.
A swarm controller dispatches phases to worker nodes; each node runs a different agent harness against a different provider, and they coordinate over a message mesh. The controller never calls a model itself — execution, cost capture, and per-user credentials live on the nodes. That separation is what makes the platform portable to an on-prem or air-gapped landscape instead of a vendor's cloud.
Applications are packaged, not hardcoded: each is a manifest that contributes its own ticket types, bots, and cockpit surface, and installs from the open store. They are grouped into five suites by who the work serves — the same runtime underneath every one of them.
Knowledge work: retrieval over your own corpus, recall across your own history, and interactive formats built on the same engine.
Market research, strategy evaluation, and an autonomous paper-trading desk that publishes its own end-of-session briefing.
The daily work surface: mail and messaging triage, document and deck generation, files, identity, and payments.
Everything outside the workday: the connected home, spatial capture, travel and transport, media, and meals.
The engineering suite: incident triage and root-cause analysis, DevOps and secrets, security review, and visual workflow authoring that compiles to a real runtime queue.
The store is open and the packaging format is documented. An operator interview produces a packed single-purpose bot — persona, manifest, and surface — and external agent skills import into the same shape.
Open a real oshal app as a guest — no signup, no card. These run on our own oshal deployment; a guest session is fully interactive for a few hours and then clears itself. Sign in to keep your work and connect your own accounts.
The natural-language front door to the whole platform. Ask it a question and it classifies the intent, delegates to the right bot, and answers — the same assistant a signed-in operator uses to drive the swarm.
The Intelligent Finance suite running against a live paper account — the real open book, average cost and unrealized P&L, the strategy sleeves, and the desk's own end-of-session recaps. Paper-traded: no live capital, and nothing here is investment advice.
A tutoring suite: a classroom of subject bots that answer questions, ground their explanations in a course corpus, track assignments, and keep a study timeline. Ask the tutor a question and watch a real reasoning turn run.
An AI game master runs a tabletop adventure — narrating scenes, offering choices, rolling dice, and keeping the campaign timeline. It shows an app owning its own domain: a persona, a store of state, and a cockpit surface over it.
The desk writes its own end-of-session briefing: results and return since inception, what triggered each position, market sentiment, and the open book — assembled into a deck and narrated, with no human in the loop. This is the platform generating a finished artifact, not a dashboard.
One prompt, several models, side by side: cost, tokens, latency, and answer quality. This is the platform's provider-neutrality made visible — the same request routed across harnesses so a team can choose a model on evidence instead of habit.
The core runtime is public under AGPL-3.0 and the application store is a separate open repository. The controls deck documents how AI-assisted work is coordinated here — explicit roles, routing, cost visibility, and review gates before anything is called done.
About these demonstrations. The guest apps open our own oshal deployment; a guest session is interactive for a few hours, then clears. They are prototypes and research systems, not production federal systems. The trading desk is paper-traded — no live capital, and nothing here is investment advice. Our earlier standalone prototypes (voice intake, workforce matching, AI planning) have been retired as their capabilities moved into oshal suites; the browser speech-control agent is currently offline. For a guided technical walkthrough or teaming discussion, contact us →
Real open positions from the paper book — average cost and unrealized P&L, refreshed every minute — plus the archive of the desk's generated session recaps. Paper-traded; every fill ties back to the signal that justified it.