I haven't written about Boomi in a while. That was a mistake. Sometime in the first quarter of 2026, while competitors were publishing connector counts and throughput benchmarks, Boomi stopped calling itself an integration company. The new label is "data activation company," and the rebrand isn't cosmetic. It changes who Boomi competes with, what budget it fights for, and which executives it needs in the room.
Integration Platform as a Service was a fight against MuleSoft and a handful of mid-market players. Data activation is a fight against Databricks, Snowflake, and the hyperscalers over who owns the semantic foundation AI agents need to function in production. Different fight. Higher stakes.
Boomi says it's tracking more than 75,000 AI agents running in production across its customer base. That number is unaudited and vendor-supplied, so take it accordingly. But earlier this year, Boomi's own published content referenced 50,000 deployed agents. Even if the 75,000 figure is soft, the direction is clear: enterprises are deploying agents faster than they can govern them, and the data problems those agents create are compounding.
I'm heading to Boomi World 2026 in Chicago in a few weeks. The company has been shipping at a pace that caught my attention, and I want to see how the data activation story holds up against customer evidence. Here's what I'm watching.
Meta Hub: A System of Record for What Your Data Means
In March 2026, Boomi launched Meta Hub. It's the most strategically interesting product the company has shipped in years, and it solves a problem that sounds boring until you realize it breaks everything downstream. Your Customer Relationship Management system defines "customer" as anyone who signed a contract. Your data warehouse counts anyone who made a purchase. Your support platform counts anyone who opened a ticket. A human can reconcile those differences over coffee. An AI agent pulling data across all three to generate a revenue forecast cannot. It will produce a confident, wrong number.
Meta Hub centralizes business definitions across enterprise systems so that when an agent queries what "revenue" means for a given business unit, it gets one answer, every time, regardless of which system it reads. One agent with a bad definition is a data quality ticket. Fifty agents, each interpreting the same term differently, running automated decisions across your enterprise? That's a systemic failure waiting to surface in a board meeting.
Two years of AI experiments across the industry, and the companies pulling ahead are the ones that fixed data trust while everyone else tuned prompts.
Steve Lucas, Boomi's Chairman and CEO, put it bluntly in the March announcement: "Organizations don't need more pilots, they need action-ready data." Two years of AI experiments across the industry, and the companies pulling ahead are the ones that fixed data trust while everyone else tuned prompts.
Where Boomi Thinks It Fits in the Agentic Stack
Boomi published a six-layer framework for enterprise AI agent architecture: Application, Orchestration, Agent, Context, Data, and Model. Each layer carries its own governance requirements. The Application layer handles interfaces and API endpoints. Orchestration coordinates workflows and routing. The Agent layer holds individual AI agents with specific capabilities. Context maintains session state and conversation history. Data manages training data, operational data, and compliance logs. The Model layer runs the large language models and inference engines.
Pay attention to where Boomi places itself. Not at the Model layer, where Microsoft, Google Cloud, and Amazon Web Services have structural advantages nobody is going to overcome. Boomi is claiming Context, Data, and Orchestration. Translation: we don't build the models, we make sure the models have the right data, the right definitions, and the right guardrails to run in production.
Agentstudio, Boomi's agent lifecycle management product, now supports native Model Context Protocol and exposes more than 300,000 endpoints as Model Context Protocol interfaces. That's the breadth of enterprise systems an AI agent can reach through Boomi's governance layer without writing custom integration code. The platform tracks agents from more than 30 providers through centralized observability, monitoring latency, errors, and token consumption in real time.
What Shipped: January Through April 2026
Read the product releases from the past four months as a group, not as individual announcements. Two threads run through all of them: making agents more governable, and making data more accessible to agents.
| Release | What It Does | Why It Matters |
|---|---|---|
| AI Agent Recommendations | Analyzes existing integrations and 200+ million patterns to suggest agents tailored to your environment | Cuts the blank-canvas problem when teams don't know which agent to build first |
| Agent Control Tower Session Logs | Surfaces chain-of-thought reasoning for every agent action | Ops teams can audit why an agent did what it did, not just what it did |
| Snowflake Cortex Provider | New provider in Agent Control Tower with External OAuth support | Connects Snowflake's AI capabilities into Boomi-governed agent workflows |
| Boomi for SAP v2.0 | Real-time SAP extraction with change data capture, multi-table ingestion, granular filtering | Gets SAP data to agents and analytics platforms without custom development |
| AWS Bedrock Connector (GA) | Production-ready connection to Amazon Web Services Bedrock generative AI models | Pulls AWS foundation models into integration workflows without custom code |
| European Platform Instance | Regionally independent instance keeping data, metadata, and runtime within EU boundaries | Clears General Data Protection Regulation residency requirements most competitors haven't addressed yet |
| Global Variables (GA) | Enterprise-wide variable governance across integration estates | Kills configuration drift when multiple teams manage hundreds of integration flows |
| PII Protection Agent | AI agent that detects and protects personally identifiable information in integration flows | Addresses the compliance exposure created when agents access sensitive data at scale |
The European Platform Instance is worth a closer look. This isn't a data center expansion. It's a regionally independent instance where customer data, metadata, and runtime execution stay within European boundaries under the General Data Protection Regulation. If you're selling into the EU and running AI agents that touch customer data, this is a procurement gate. Most competing platforms haven't cleared it.
One more: Boomi now ships an agent that writes integration documentation automatically. If you've managed a large integration estate, you know documentation debt is the thing everyone acknowledges and nobody fixes. An agent that maintains it on its own is a small feature that solves a real, persistent operational problem.
What I'm Looking For at Boomi World (May 11-14, Chicago)
Boomi World 2026 runs May 11 through 14 at the Hyatt Regency Chicago. I'll be there. The declared theme is data activation powering AI, analytics, and intelligent automation in what Boomi calls an "increasingly agentic world." Every platform vendor is claiming the agentic world right now. What I want to see is what makes Boomi's version different from what you already get from your cloud provider.
Skip the keynote roadmap slides. The sessions on agent governance and Meta Hub implementation at enterprise scale are where the signal is. If Boomi can put customers on stage who used Meta Hub to reduce AI agent error rates or cut time-to-production for agentic workflows, the data activation thesis holds. If the case studies are still in pilot, that's a different conversation.
I'm also watching hyperscaler partnership announcements. AWS Bedrock reaching general availability and the Snowflake Cortex provider suggest Boomi wants to be the governance and activation layer sitting above hyperscaler AI services, not competing with them. If that positioning gets reinforced at Boomi World with joint announcements, it reshapes the competitive story. I'll be writing more from the event at shashi.co.
Boomi has 30,000 customers, 800 partners, private-equity backing, and a valuation in the $4 billion range. The engineering depth to execute the data activation vision is there. Execution isn't the risk.
Timing is. Microsoft, Amazon Web Services, and Google Cloud are all building agent orchestration with their own data layers and governance models. Databricks and Snowflake are pushing hard into semantic layers. All of them have distribution advantages a private-equity-backed vendor can't match on reach or bundling.
Can Boomi establish enough ownership of the agentic data layer before Amazon, Microsoft, and Google decide "data activation" is a feature they ship inside their own platforms rather than a category they partner on? The 75,000 agents and 300,000 Model Context Protocol endpoints say Boomi has more production evidence than most. Whether that's enough, and whether the window stays open long enough, is what I'm going to Chicago to find out.
