Why Brex Thinks the Future of AI Isn’t More Orchestration — It’s Less
Inside the fintech’s bold bet on an “Agent Mesh” for autonomous finance
In the race to automate enterprise work with AI, most builders have doubled down on orchestration — centralized frameworks that coordinate AI agents through rigid workflows and deterministic paths. But Brex, the fintech known for reimagining corporate finance, is charting a different course: less orchestration, more autonomy. ([Venturebeat][1])
Rather than funneling every task through a central controller, Brex CTO James Reggio says the future lies in a decentralized network of specialized agents — each with a narrow, clearly defined role — that communicate freely and operate independently. This “Agent Mesh” is already powering a new generation of autonomous financial automation in Brex’s platform, aiming to make expense management and financial operations effectively invisible to users. ([Venturebeat][1])
From Copilots to Autonomous Agents
Brex’s AI journey began with its Brex Assistant, launched in 2023. This generative AI feature helped customers automate routine tasks like expense submission and policy compliance. It combined models from Anthropic, custom Brex tooling, and OpenAI’s APIs to streamline basic workflows. ([Venturebeat][1])
But for Reggio and his team, it soon became clear that this assistant was still too limited — useful, but far from fully autonomous. The next step, they realized, demanded rethinking how AI agents interact, respond to context, and execute complex, multi-step processes without human oversight. ([Venturebeat][1])
What Makes an “Agent Mesh” Different
Traditional orchestration systems treat AI workflows like static pipelines — central coordinator, pre-defined steps, and enforced sequences. Brex argues this model can become a bottleneck as agents become more capable. ([Venturebeat][1])
By contrast, the Agent Mesh is:
- Distributed — no single orchestrator; agents manage their own tasks
- Role-Specific — each agent focuses on one narrow responsibility
- Message-Driven — agents communicate in natural language via a shared message stream
- Adaptive — routing models decide which tools each agent needs in real time ([Venturebeat][1])
Think of it like a Wi-Fi mesh network — no central hub, yet the system as a whole remains reliable through overlapping nodes that collaborate fluently. ([Venturebeat][1])
A reimbursement request, for example, could trigger multiple agents — compliance checker, budget evaluator, receipt matcher, and payment initiator — all contributing to a seamless outcome without a rigid workflow dictating every step. ([Venturebeat][1])
Built-In Safety and Visibility
Decentralized doesn’t mean uncontrolled. Brex layers in audit and evaluation agents that review decisions for accuracy and policy compliance, and a global message log (“MessageStream”) tracks every action. A central “Clock” component ensures actions happen in a deterministically ordered timeline. ([Venturebeat][1])
This hybrid approach — modular autonomy with auditability — addresses key enterprise concerns about reliability, transparency, and governance as AI systems take on more responsibility. ([Venturebeat][1])
Early Results — and Big Ambitions
Brex isn’t yet sharing detailed third-party benchmarks, but according to Reggio, customers are hitting 99% automation in workflows that once required manual oversight — up from 60–70% pre-AI. The goal isn’t just to automate tasks faster, but to make employees stop thinking about finance workflows at all. ([Venturebeat][1])
This shift reflects a broader trend in enterprise AI: as models grow more capable and better at reasoning and tool use, the orchestration layer itself must evolve from strict control plane to flexible, emergent ecosystem. Brex hopes its Agent Mesh approach will lead the way. ([Venturebeat][1])
Glossary
Agent Mesh A decentralized network of AI agents, each specialized in a narrow task, communicating via a shared message stream instead of a central orchestrator. ([Venturebeat][1])
Orchestration (Traditional) A controlled system where a central coordinator choreographs workflows and agents via predefined, deterministic paths. ([Venturebeat][1])
Deterministic Ordering A guarantee that events occur in a predictable sequence, useful for traceability and debugging in autonomous systems. ([Venturebeat][1])
Audit Agent An AI component tasked with verifying decisions made by other agents against policy and accuracy standards. ([Venturebeat][1])
| [1]: https://venturebeat.com/orchestration/brex-bets-on-less-orchestration-as-it-builds-an-agent-mesh-for-autonomous “Brex bets on ‘less orchestration’ as it builds an Agent Mesh for autonomous finance | VentureBeat” |
