Exclusive: Omni raises $120 million to fix one of AI’s biggest enterprise data problems

```json { "title": "Omni Raises $120M to Solve Enterprise AI Data Problem", "metaDescription": "Omni Analytics hits $1.51B valuation after raising $120M backed by ICONIQ, building the semantic layer AI agents need to deliver reliable enterprise insights.", "content": "<h2>Omni Reaches Unicorn Status With $120 Million Raise Targeting Enterprise AI's Semantic Layer Problem</h2><p>San Francisco-based analytics startup Omni has raised $120 million in a new funding round backed by ICONIQ, according to a Fortune exclusive published on April 23, 2026, pushing the company's valuation to $1.51 billion and officially making it a unicorn. The raise comes as enterprises grapple with a fundamental and growing problem: AI systems that fail not because the models are inadequate, but because the underlying data lacks the semantic consistency those models need to produce reliable results. Omni's platform, built around a central semantic layer, is designed to fix exactly that.</p><p>Founded in 2022 by Colin Zima, Chris Merrick, and Jamie Davidson — a team with deep roots at Looker, the business intelligence company acquired by Google — Omni has scaled quickly in a market increasingly defined by enterprise AI adoption. The company's arc from its $26.9 million public launch in August 2022 to a $1.51 billion valuation in 2026 reflects both its own execution and a broader industry reckoning with what it actually takes to make AI work inside large organizations.</p><h2>What the $120 Million Round Means for Omni</h2><p>The April 2026 raise is Omni's largest to date and represents a significant step up from its previous funding milestones. In March 2025, ICONIQ Growth led a $69 million Series B that valued the company at $650 million — itself a milestone achieved on the company's third birthday, accompanied by 8x year-over-year growth in both revenue and customer usage. Prior to the reported April 2026 round, Omni had raised approximately $95.9 million in total across multiple rounds since its 2022 founding.</p><p>ICONIQ Growth's continued backing through this new round underscores the firm's conviction in Omni's approach. The new valuation of $1.51 billion nearly doubles the $650 million mark set just over a year earlier. While the Fortune report is based on an exclusive and had not yet been independently confirmed by secondary sources at the time of publication, it aligns with the growth trajectory Omni has publicly documented.</p><p>On the revenue side, Omni projected annual recurring revenue of $30 million by the end of 2025, representing 4x year-over-year growth following 10x growth in 2024. The company expected to double ARR again in 2026, driven by growing demand for a unified analytics platform. In October 2025, Omni added meaningful product surface area through its acquisition of Explo, a leading embedded analytics company that became a wholly owned subsidiary, extending Omni's reach into customer-facing analytics use cases.</p><p>At the time of its Series B in March 2025, Omni had over 200 customers, including Perplexity, BuzzFeed, and Writer, and was planning to grow its headcount from 85 employees to 150 by the end of 2025. The company's investor base spans some of the most active names in enterprise software and data infrastructure: ICONIQ Growth, Theory Ventures, First Round Capital, Redpoint Ventures, GV, Snowflake Ventures, and Databricks Ventures.</p><h2>The Semantic Layer: Why It Matters for Enterprise AI</h2><p>To understand why Omni is attracting this level of investment, it helps to understand what a semantic layer actually does — and why it has become critical infrastructure for enterprise AI deployments in 2025 and 2026.</p><p>A semantic layer sits between raw enterprise data and the people or AI systems querying it. It centralizes business logic — metric definitions, table joins, access controls, naming conventions — so that every query, whether typed in SQL by a data analyst, clicked through a dashboard, or generated by an AI agent using natural language, returns results built on the same underlying definitions. Without this layer, different teams, tools, and AI systems may interpret the same underlying data differently, producing inconsistent or contradictory outputs.</p><p>This is not a theoretical problem. A March 2026 report from Cloudera and Harvard Business Review Analytic Services found that only 7% of enterprises say their data is completely ready for AI. Separately, Gartner has forecast that more than 40% of agentic AI projects will be abandoned by 2027 due to unclear outcomes and poor integration. And according to Forrester research, 61% of organizations currently use four or more business intelligence tools, with 25% using ten or more — a fragmentation that makes consistent semantic definitions across AI agents nearly impossible without a governing layer.</p><p>Gartner has also predicted that by 2027, organizations that prioritize semantics in their AI-ready data architecture will increase generative AI model accuracy by up to 80% and reduce costs by up to 60%. These projections place semantic infrastructure at the center of enterprise AI strategy, not at the periphery.</p><p>Omni's platform addresses this directly. Rather than requiring enterprises to choose between human analytics and AI-powered querying, Omni supports multiple interfaces — SQL, natural language AI, spreadsheets, and point-and-click dashboards — all governed by the same semantic layer. On the AI infrastructure side, Omni uses AWS Bedrock-hosted Claude models for most tasks and OpenAI models for advanced AI visualizations; the company does not operate its own large language model.</p><h2>A Team Built From Looker's DNA</h2><p>Omni's founding team is frequently described in terms of its Looker lineage, and that context matters. Looker was among the first analytics platforms to popularize the concept of a modeling layer — what it called LookML — that centralized metric definitions across an organization. Google acquired Looker in 2020. The founders of Omni, who came out of that environment, built their new company explicitly around extending that same philosophy into the era of AI agents and embedded analytics.</p><p>Omni describes itself, per Santa Cruz Works, as a startup filled with ex-Looker talent focused on building a business intelligence and embedded analytics platform. That institutional knowledge of how enterprises actually manage data — and where the semantic consistency breaks down — is part of what has shaped Omni's product architecture and customer traction.</p><h2>What Investors and the CEO Have Said</h2><p>The verified statements from Omni's leadership and its lead investor provide a clear picture of how both sides frame the company's market position.</p><p>Matt Jacobson, Partner at ICONIQ, offered a pointed view on what separates successful AI analytics from failed ones: <em>"AI success in analytics is not about crafting better prompts – it is about building deep context into the data itself. Omni is purpose-built to deliver exactly that."</em> In a separate statement, Jacobson noted: <em>"Omni's ability to pair strong growth with real product velocity and operational discipline is rare."</em></p><p>Colin Zima, Omni's CEO and co-founder, articulated the platform's technical value proposition directly: <em>"Omni's semantic layer grounds AI outputs in a solid data foundation, so whether you're using natural language, SQL, or any other interface, you get reliable insights."</em> On the Explo acquisition, Zima noted the quality of the team they were bringing in: <em>"The Explo team built a product customers love in a crowded market — that's not easy, and it says a lot about their quality and focus."</em></p><h2>What Comes Next</h2><p>With $120 million in fresh capital and a $1.51 billion valuation, Omni enters 2026's second half with significant runway to expand its platform, its team, and its customer base. The company had already signaled intent to double ARR in 2026 before this round was reported, and the new capital provides additional leverage for product development, sales expansion, and potentially further acquisitions along the lines of the Explo deal.</p><p>The broader market dynamics suggest the timing is deliberate. Enterprise AI adoption is accelerating, but the failure rate of AI data projects remains high. As organizations move from AI experimentation toward production deployment of AI agents — systems that must query data autonomously and consistently — the demand for a reliable semantic layer is likely to grow. Omni is positioning itself as the infrastructure layer that makes agentic AI in analytics actually work.</p><p>That said, the competitive landscape for business intelligence and semantic layer tooling is not static. Established players and well-funded startups are all converging on similar architectural conclusions about the necessity of centralized data semantics for AI. Omni's differentiation will depend on continued product execution, the depth of its integrations with data platforms backed by its own investors — including Snowflake and Databricks — and its ability to serve both the human analyst and the AI agent with equal reliability.</p><p>The April 2026 raise positions Omni to compete at a higher level. Whether the $1.51 billion valuation proves conservative or aggressive will depend on how quickly enterprises move to standardize on semantic infrastructure — and how effectively Omni can capture that wave.</p><p>For more tech news, visit our <a href=\"/news\">news section</a>.</p><h2>Why This Matters for How You Work</h2><p>The problems Omni is solving — fragmented data, inconsistent metrics, AI outputs you can't trust — aren't just enterprise headaches. They reflect a broader challenge facing anyone who relies on data tools to make decisions, manage time, or optimize performance. As AI agents become embedded in productivity and health platforms, the quality of the underlying data layer will directly determine whether those tools help you make better decisions or simply generate confident-sounding noise. At Moccet, we believe that reliable data infrastructure is the foundation of any tool worth using — whether you're tracking your health, managing your focus, or building a business. <a href=\"/#waitlist\">Join the Moccet waitlist to stay ahead of the curve.</a></p>", "excerpt": "Omni Analytics has raised $120 million in a new funding round backed by ICONIQ, reaching a $1.51 billion valuation as it builds the semantic layer infrastructure enterprises need to make AI agents work reliably. The San Francisco startup, founded in 2022 by ex-Looker veterans, has grown from a $650 million valuation in March 2025 on the back of 10x ARR growth in 2024 and a projected doubling of revenue in 2026. The raise arrives as industry research shows only 7% of enterprises consider their data fully AI-ready.", "keywords": ["semantic layer", "enterprise AI", "Omni Analytics", "business intelligence", "AI data infrastructure"], "slug": "omni-raises-120-million-semantic-layer-enterprise-ai" } ```