Bobsled
Bobsled, Inc., founded in 2021 by CEO Jake Graham (a former Microsoft Azure, Neo4j, and Intel executive) and a team of co-founders, is a Los Angeles-based infrastructure company.
Profile
Bobsled provides a platform that lets data teams build AI agents and analytics agents that answer questions from complex datasets, replacing traditional dashboards.
Bobsled, Inc., founded in 2021 by CEO Jake Graham (a former Microsoft Azure, Neo4j, and Intel executive) and a team of co-founders, is a Los Angeles-based infrastructure company. It has raised $24 million to date: a $7 million seed round led by .406 Ventures and a $17 million Series A in April 2023 co-led by Greycroft and Madrona Venture Group at an $87 million valuation. The company originally built a cross-cloud data sharing platform that allowed data providers to publish data from any cloud to any destination without managing subscriptions.
As of mid-2026, Bobsled has pivoted its product portfolio to focus on AI agents and analytics agents, positioning itself as a "#1 Data Products Platform" that helps data teams turn data into AI experiences. Its website now markets an "Analytics Agent" that lets users analyze complex data without SQL, and "Agentic Workflows" for external agents to answer questions. Customer logos on its site include ZoomInfo, Deutsche Börse Group, LSEG, Dun & Bradstreet, Facteus, CARTO, GlobalData, Lightcast, Cotality, Uniphore, and Shovels.
The company has not disclosed revenue, headcount, or any funding rounds since 2023. Its shift from a data-sharing middleware play to an AI agent platform reflects the broader market rush toward generative AI, but also raises questions about product maturity and competitive differentiation in a crowded space.
Who buys this
- Data providers and data-as-a-service companies that need to share data products with customers
- SaaS companies embedding analytics or AI workflows into their products
- Large enterprises with multi-cloud data environments (e.g., Snowflake, Databricks, AWS, Azure)
- Financial services and market data firms (e.g., Deutsche Börse, LSEG, Dun & Bradstreet)
Publicly disclosed clients
- ZoomInfo
- Deutsche Börse Group
- LSEG
- Dun & Bradstreet
- Facteus
- CARTO
- GlobalData
- Lightcast
- Cotality
- Uniphore
- Shovels
Strengths and what to watch
Strengths
- Named customer logos include major financial data and analytics firms (Deutsche Börse, LSEG, Dun & Bradstreet), indicating enterprise traction in regulated verticals.
- Raised $24 million from tier-1 investors (Greycroft, Madrona, Salesforce Ventures, Tiger Global) at an $87 million valuation, providing a credible capital base.
- Product pivot to AI agents aligns with the 2025-2026 market demand for agentic AI, potentially opening new revenue streams beyond the original data-sharing use case.
Watch for
- No disclosed funding since April 2023; the company may be operating on existing capital or struggling to raise a Series B in a tighter venture market.
- Product pivot from cross-cloud data sharing to AI agents is a significant strategic shift; it is unclear if the original customer base is adopting the new products or if the company is chasing a new market.
- The website lists many customer logos but provides no case studies, revenue figures, or independent validation of product usage; claims of "time to insight" are anecdotal and not backed by published benchmarks.
Key Information
- Industry
- Data Integration
- Founded
- 2021
- Headquarters
- Los Angeles
Frequently Asked Questions
What is Bobsled and what does it do?
Bobsled is a Los Angeles-based infrastructure company founded in 2021. It provides a platform for data teams to build AI agents and analytics agents that answer questions from complex datasets, replacing traditional dashboards. It has raised $24 million from investors like Greycroft and Madrona.
How does Bobsled's analytics agent work?
Bobsled's analytics agent lets users analyze complex data without writing SQL. It uses AI to answer questions from datasets, aiming to replace traditional dashboards. The platform also supports agentic workflows for external agents to query data, targeting data teams and SaaS companies.
Who are Bobsled's main customers?
Bobsled's customers include major financial data firms like Deutsche Börse Group, LSEG, and Dun & Bradstreet, as well as ZoomInfo, Facteus, CARTO, GlobalData, Lightcast, Cotality, Uniphore, and Shovels. These span data providers, SaaS companies, and large enterprises with multi-cloud environments.
How much funding has Bobsled raised and from whom?
Bobsled has raised $24 million total: a $7 million seed round led by .406 Ventures and a $17 million Series A in April 2023 co-led by Greycroft and Madrona Venture Group at an $87 million valuation. Investors also include Salesforce Ventures and Tiger Global.
What was Bobsled's original product before the pivot?
Bobsled originally built a cross-cloud data sharing platform that let data providers publish data from any cloud to any destination without managing subscriptions. As of mid-2026, it pivoted to focus on AI agents and analytics agents, rebranding as a data products platform.
Is Bobsled's AI agent platform proven with case studies?
Bobsled's website lists customer logos but provides no case studies, revenue figures, or independent validation of product usage. Claims about time to insight are anecdotal and not backed by published benchmarks, raising questions about product maturity in a competitive market.
Sources
- bobsled.it — Current product positioning as AI agent platform, customer logos, and tagline 'Agents are the new dashboards'.
- techcrunch.com — Series A funding details: $17M, co-led by Greycroft and Madrona, $87M valuation, seed round led by .406 Ventures.
- startupintros.com — Total funding $24M, founding date 2021, CEO Jake Graham background, and investor list including Salesforce Ventures and Tiger Global.
- bobsled.it — Customer logos (ZoomInfo, Deutsche Börse, LSEG, Dun & Bradstreet, Facteus, CARTO, GlobalData, Lightcast, Cotality, Uniphore, Shovels) and testimonial quotes from Scott Morrison (DaaS) and Steven Pham (Cotality).