Fintech Brex is betting that the way forward for enterprise AI isn’t higher orchestration — it’s much less of it.
As generative AI brokers transfer from copilots to autonomous techniques, Brex CTO James Reggio says conventional agent orchestration frameworks have gotten a constraint somewhat than an enabler. As an alternative of counting on a central coordinator or inflexible workflows, Brex has constructed what it calls an “Agent Mesh”: a community of slender, role-specific brokers that talk in plain language and function independently — however with full visibility.
“Our aim is to make use of AI to make Brex successfully disappear,” Reggio informed VentureBeat. “We’re aiming for complete automation.”
Brex discovered that for its functions, brokers must work in slender, particular roles to be extra modular, versatile, and auditable.
Reggio mentioned the architectural aim is to allow each supervisor in an enterprise “to have a single level of contact inside Brex that’s dealing with the totality of their duties, be it spend administration, requesting journey, or approving spend restrict requests.”
The journey from Brex Assistant
The monetary providers trade has lengthy embraced AI and machine studying to deal with the huge quantities of information it processes. However relating to bringing AI fashions and brokers, the trade took a extra cautious street in the beginning. Now, extra monetary providers firms, together with Brex, have launched AI-powered platforms and a number of agentic workflows.
Brex’s first foray into generative AI was with its Brex Assistant, launched in 2023, which helped clients automate sure finance and expense duties. It gives options to finish bills, routinely fills in info, and follows up on bills that violate insurance policies.
Reggio acknowledges that Brex Assistant works, however it’s not sufficient. “I believe to some extent, it stays a little bit of a know-how the place we don't totally know the boundaries of it," he mentioned. "There's fairly numerous patterns that must exist round it which might be sort of being developed by the trade because the know-how matures and as extra firms construct with it."
Brex Assistant makes use of a number of fashions, together with Anthropic’s Claude and customized Brex-models, in addition to OpenAI’s API. The assistant automates some duties however continues to be restricted in how low-touch it may be.
Reggio mentioned Brex Assistant nonetheless performs a giant function within the firm’s autonomy journey, primarily as a result of its Agent Mesh product flows into the appliance.
Agent Mesh to interchange orchestration
The consensus within the trade is that multi-agent ecosystems, during which brokers talk to perform duties, require an orchestration framework to information them.
Reggio, alternatively, has a unique take. "Deterministic orchestration infrastructure … was an answer for the issues that we noticed two years in the past, which was that brokers, similar to the fashions, hallucinate loads,” Reggio mentioned. “They're not superb with a number of instruments, so it’s worthwhile to give them these levels of freedom, however in a extra structured, inflexible system. However because the fashions get higher, I believe it's beginning to maintain again the vary of prospects which might be increasing.”
Extra conventional agent orchestration architectures both deal with a single agent that does every thing or, extra generally, coordinator/orchestrator plus software brokers that explicitly outline workflows. Reggio mentioned each frameworks are too inflexible and resolve points extra generally seen in conventional software program than in AI.
The distinction, Reggio argues, is structural:
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Conventional orchestration: predefined workflows, central coordinator, deterministic paths
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Agent Mesh: event-driven, role-specialized brokers, message-based coordination
Agent Mesh depends on stitching collectively networks of many small brokers, every specializing in a single job. The brokers, as soon as once more utilizing the hybrid mixture of fashions as with the Brex Assistant, talk with different brokers “in plain English” over a shared message stream. A routing mannequin shortly determines which instruments to invoke, he mentioned.
A single reimbursement request triggers a number of duties: a compliance examine to align with expense insurance policies, price range validation, receipt matching, after which fee initiation. Whereas an agent can actually be coded to do all of that, this technique is “brittle and error-prone,” and it responds to new info shared by a message stream anyway.
Reggio mentioned the concept is to disambiguate all of these separate duties and assign them to smaller brokers as a substitute. He likened the structure to a Wi-Fi mesh, the place no single node controls the system — reliability emerges from many small, overlapping contributors.
“We mainly discovered a extremely good match with the concept of embodying particular roles as brokers on high of the perfect platform to handle particular duties, very similar to the way you would possibly delegate accounts payable to at least one workforce versus expense administration to a different workforce,” Reggio mentioned.
Brex defines three core concepts within the Agent Mesh structure:
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Config, the place definitions of the agent, mannequin, instruments and subscription stay
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MessageStream, a log of each message, software name and state transition
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Clock, which ensures deterministic ordering
Brex additionally constructed evaluations into the system, during which the LLM acts as a decide, and an audit agent opinions every agent’s choices to make sure they adhere to accuracy and behavioral insurance policies.
Success to date
Brex says it has seen substantial effectivity positive factors amongst its clients in its AI ecosystem. Brex didn’t present third-party benchmarks or customer-specific information to validate these positive factors.
However Reggio mentioned enterprise clients utilizing Brex Assistant and the corporate’s machine studying techniques “are in a position to obtain 99% automation, particularly for patrons that basically leaned into AI.”
This can be a marked enchancment from the 60 to 70% Brex clients who have been in a position to automate their expense processes earlier than the launch of Brex Assistant.
The corporate continues to be early in its autonomy journey, Reggio mentioned. But when the Agent Mesh strategy works, probably the most profitable final result could also be invisible: workers not enthusiastic about bills in any respect.
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