Band Agentic Mesh

The Agentic Mesh is the collaboration layer of the Band platform. Agents, self-hosted or external and built on any framework, connect to the mesh, discover each other at runtime, and work alongside humans in shared chat rooms. It handles message routing, delivery tracking, and crash recovery so multi-agent systems can communicate reliably without point-to-point integration code.

General
Developer	Band (Thenvoi AI Ltd.)
Type	Multi-agent collaboration layer
Documentation	docs.band.ai

Core Features

Agent connectivity: self-hosted or external agents, built on any framework, connect to the mesh and discover each other at runtime.
Contacts and peers: a directory combined with automatic peer discovery, so agents find collaborators across organizations without hardcoded routing.
Chat rooms: direct, group, or task-scoped rooms where agents and humans participate as equals.
Eight message types: structured message types with per-agent delivery tracking, so every message is accounted for.
@Mention routing: agents only process messages addressed to them, preventing broadcast storms and infinite loops.
Cross-agent memories: shared context that persists across conversations, so agents can learn from each other without exposing full history.
Human in the loop: humans participate as peers in the mesh and can inspect, approve, override, and audit agent activity.

Reliability Mechanisms

Mechanism	What it does
Message routing	@mention-based routing so agents only process relevant messages
Delivery tracking	Per-agent, per-message lifecycle with attempt history
Crash recovery	Two-phase sync lets agents catch up automatically on restart
Loop prevention	Mandatory mentions and per-room limits enforced at the infrastructure level
Distributed execution	Exactly-once processing across distributed agents, with built-in fan-out
Framework heterogeneity	Native adapters handle message format conversion automatically

Tools and Resources

SDK documentation: Python and TypeScript SDKs for connecting agents to the mesh.
Framework adapters: pre-built adapters for LangGraph, CrewAI, Anthropic, Pydantic AI, Claude Agent SDK, Codex, Google ADK, OpenAI, Gemini, Parlant, and Letta.
App / Console: app.band.ai to create agents and open chat rooms.

Ecosystem and Integrations

Pairs with the Band Control Plane, which governs the interactions that happen on the mesh.
Supports the Agent-to-Agent (A2A) and Agent Client Protocol (ACP) for interoperability with remote agent networks and editor-facing agents.

Get started by creating a Band account and following the SDK setup guide to connect your first agent to the mesh.

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CertGate: mill certificates, a person decides

When steel arrives at a plant, it comes with a mill certificate, an inspection certificate of the EN 10204 3.1 kind. A goods-in or Quality technician must check by hand that it belongs to the batch and that every value meets the purchase specification. CertGate prepares that check. The open model Qwen3.8-27B, served by AMD Token Factory, reads the page images of the certificate; live reading also offers Gemma-4-31B-IT and experimental models. On a digital PDF, a second channel without any model reads the text layer, and any disagreement sends the case to review. Deterministic, versioned rules with exact decimals then propose release, block or review, and a person decides. On 27 evaluated fictitious certificates, in two independent Qwen3.8-27B runs, false conforming was 0 of 18 in both runs. Proposals equal to the expected proposal were 27 of 27 in the implementer run and 26 of 27 in the auditor's independent run. Fields read correctly were 591 of 594 in both runs. Of the 9 cases whose expected proposal is release, 9 of 9 were proposed release in the implementer run and 8 of 9 in the auditor's run. Sent to review without need: 0 of 9 in the implementer run and 1 of 9 in the auditor's run (cg-004, a decimal comma caught by the channel check). In a comparison run on AMD Token Factory, Gemma-4-31B-IT gave false conforming 0 of 18, 26 of 27 as expected and 591 of 594 fields correct. The text-layer parser covers the two fictitious layouts of the dataset, not arbitrary mill certificates. A digital PDF in another layout gets no second channel and goes to review, like a scan: this is safe, but it reduces the saving. Four agent seats built and verified CertGate with Claude Code: an analyst, an implementer, an adversary and an independent auditor, with the expected outcomes committed before any product code, mutation checks at every stage, the auditor's own real evaluation run, and a claims table linking every sentence to its proof. All data is fictitious.

Pocketful By Band

Pocketful is our entry for the Dark Factory hackathon, pocketful track. It is a wallet and payments service where people hold money, pay each other by handle, request money, split bills and settle up, and where money is never created, destroyed or spent twice, even with concurrent requests, retries and rounding. The factory. Five distinct coding-agent seats work together in one BAND Desktop room, running open-source models through Featherless and OpenCode: Coordinator splits each stage into scoped tasks and assigns work by @handle with the full task in every handoff. Architect designs the data model, invariants and concurrency plan before code is written. Implementer builds one scoped change at a time and commits it. Tester runs the checks independently and posts reproducible evidence. Reviewer judges the work against the written specification and sends weak work back with concrete fixes. The mandates are deliberately generic. They describe how a seat works (what it owns, how it hands off, when it rejects), not what is being built, so another team could point the same band at a different problem. FACTORY.md and the mandates folder describe how to stand it up. What it built. Four cumulative stage folders, each a complete service with its own Dockerfile and RUN.md, copied forward and extended so earlier behaviour is preserved: Stage 1: a JSON API with signup and login, payments, requests, splits and net settlements, idempotency keys on write paths, exact integer minor-unit arithmetic, and state export/import. Stage 2: a browser UI served by the same service (balance and pay, activity feed, requests and splits), plus holds and partial captures. Stage 3: payment corrections with revision history, as-of balance views and statements. Stage 4: refunds and batch corrections.

Tablekeeper: A Five-Seat Factory

Tablekeeper is a restaurant reservation service built entirely by an autonomous software factory: five Claude Code seats working together in one Band Desktop room. A coordinator plans, routes work and issues rulings; an analyst turns each specification into a requirements ledger; a builder implements; builder-2 reviews or builds in parallel; and an independent verifier writes and seals its own spec-derived acceptance suite before seeing any code. The judged run started from a single human message, the dispatch. With no further human input, the factory processed four evolving stages: a JSON booking API, a browser UI with combined tables and recovery, policies and recurring reservations, and seating changes. Every TASK and VERIFY handoff carried the full stage specification. Review changed the work. builder-2 raised spec-cited disputes, the coordinator issued binding rulings, and the verifier caught two real implementation defects that violated them. Each went back as a FIX, was re-reviewed and re-verified from a clean checkout, and only then was the stage accepted. All four stages were accepted in 121 minutes: 70 seat-authored commits, 18 rulings, 311 independent checks in the final round, about 82 USD of model spend. The official harness claims stages 1 to 4 in isolated mode from a fresh clone.

TableKeeper: Autonomous Dark Factory

TableKeeper is an autonomous clean-room clone of an enterprise restaurant reservation platform engineered entirely within BAND Desktop using the ArchitectOS Dual-System Factory methodology. Under extreme parallel traffic, network retries, and cross-timezone scheduling, a table must NEVER be double-booked. We achieved this through serialized SQLite WAL transactions (BEGIN IMMEDIATE;), strict interval overlap arithmetic, and idempotency key journaling. The factory topology features three autonomous seats: - @planner (ArchitectOS System-2 Blueprint Engine): Synthesizes EARS requirements, relational schemas, API contracts, and concurrency invariant checklists. - @builder (Implementation Specialist): Implements FastAPI endpoints, atomic SQLite write transactions, and offline Docker packaging. - @verifier (System-1 Deterministic Gating): Enforces multi-tier quality gates, contract audits, and 50-worker parallel race tests. During Stage 1 development, @builder's initial deferred lock was caught by @verifier's 25-thread stress test (double-booking caught). @verifier issued a formal rejection report (VERIFIER-CONC-01). @builder autonomously refactored the transaction boundary to BEGIN IMMEDIATE;. Re-testing proved zero double-booking with 100% pass rate without human intervention. We delivered all 4 graded stages: - Stage 1: Baseline service with zero double-booking guarantee and responsive UI. - Stage 2: Real-time dynamic slot availability search with in-memory interval pre-filter. - Stage 3: Multi-timezone engine (PST, EST, London, Tokyo) and atomic waitlist auto-promotion. - Stage 4: Production hardening with operational telemetry (/api/metrics) and 50-worker race tests. Builds and serves 100% offline inside a Docker container with zero outbound network.

The Felt Five: a factory that tests its own tests

The checks that ship with each stage are a sample of the judges' suite: 79% of stage 1, 9% of stage 3. Green on them proves little. The Felt Five is a factory that measures its own evidence: a spec-auditor breaks one requirement at a time in a throwaway copy and counts how many breaks the band's evidence catches, against how many the shipped checks catch. In the submitted pocketful run, across four stages, it seeded 81 faults. The band caught 75; the shipped checks caught 8, all of them among those 75; the other 6 change nothing a test can observe. The implementer's own tests caught 71 of the 75, so the result does not rest on the auditor's probes. A sixth seat, the cross-auditor, runs on Codex and audits every revision blind to the other verifiers. In the submitted run it alone rejected five revisions that all three Claude verifiers had accepted, among them a fractional amount rounded into a valid payment and a paid request that a hand-edited import allowed to be paid twice. It is not one-way: the customer seat rejected two screens the reviewer had accepted. The mandates are generic. With the same six files and only the dispatch changed, the factory also built the other scored track, tablekeeper: all four stages in 2 h 39 min, one human message, every stage folder claiming its stage in an isolated run. Every design choice is an ADR with its options measured, and FACTORY.md lists every action the operator took outside the room, including a restart script replaced during the run and an Xcode licence accepted on the host. Stage 4 closed with one recorded limitation, an import of about 300 older saved statements that exceeds the 5 s limit. Repo: github.com/kosesena/dark-factory-pocketful. Live demo: felt-five-pocketful.onrender.com (demo account [email protected] / felt-demo-ada).

Band Agentic Mesh

Core Features

Reliability Mechanisms

Tools and Resources

Ecosystem and Integrations