In 2019, David Lanstein and his co-founders started Atolio to answer a pressing question: why do employees at large organizations still struggle to find information hidden across dozens of internal systems? The company’s early research was exhaustive: Lanstein says they interviewed executives at more than 700 enterprises before writing a line of code. One manufacturing CIO told them, “80% of our orders are custom, and we have six systems that sit in front of SAP, our sales reps are sitting in the parking lot and they have no way to go tell a client the status of an order, because it could be sitting in any one of those six systems.”
That type of real-world frustration became the foundation for Atolio’s product: a secure, AI-powered search platform that aggregates information from across an enterprise’s systems without sending any data to the public cloud.
Atolio just announced it has raised $24 million in total funding, including a Series A led by Translink Capital with participation from IBM Ventures, Bloomberg Beta, Acorn Pacific Ventures, and Parameter Ventures.
Building a Search Platform Enterprises Can Trust
Atolio’s platform is designed to integrate with enterprise applications, index them in a private environment, and provide employees with a single reference point for finding answers. The company emphasizes that no data leaves the customer’s infrastructure, whether the deployment is on a private cloud, an air-gapped system, or physical servers.
Lanstein frames the mission succinctly: “A company’s knowledge is the work product of their people, and we exist to help our clients access and leverage the knowledge they have been accruing over many years to help them run better businesses and organizations.”
That positioning has found resonance in industries where security and control over data are non-negotiable. CIOs and CTOs consistently told Atolio that any system aggregating corporate knowledge had to operate under the enterprise’s control, particularly in light of risks such as data leaks, inadvertent training of public models, and data sovereignty rules that restrict where information can reside.
The emphasis on privacy differentiates Atolio from search products offered by hyperscalers or newer AI entrants that rely on centralized, cloud-hosted models. Jackie Yang, general partner at Translink Capital, put it plainly: “Atolio stands out as the only AI-powered enterprise search engine that guarantees your data stays protected in your preferred environment.”
Foundational Layer for Applications
Adoption appears strongest among large organizations where broken systems slow down frontline teams. Cengage, an education technology firm, began using Atolio to give sales and marketing employees faster access to product and customer information. CEO Michael Hansen told investors earlier this year, “We are investing in automation to drive internal efficiencies like an AI-powered search with products such as Atolio… We believe these tools will significantly increase productivity of our go-to-market teams.”
Atolio says it has closed multiple seven-figure contracts over the past three quarters, though it does not disclose customer names beyond those already public. The firm positions itself as a strategic infrastructure investment, arguing that almost every large enterprise will eventually adopt private AI-powered search. The analogy Lanstein and co-founders Gareth Watts and Mark Matta use is that Atolio could become for unstructured data what Splunk became for log data: a foundational layer on which others build specialized applications.
The market for enterprise search is crowded, with established vendors like Elastic and Microsoft offering broad tools, and newer startups experimenting with generative AI-powered discovery. Atolio’s bet is that its insistence on private, fully controlled deployments will give it an edge among financial institutions, government agencies, and multinational corporations with strict compliance requirements. That approach could also slow adoption among smaller firms that are comfortable with cloud-hosted solutions.
Scaling Distribution
The new funding will be used to expand engineering, develop additional connectors for enterprise applications, and scale distribution. IBM’s involvement signals a potential sales channel partnership, with Emily Fontaine, IBM’s global head of venture capital, describing the investment as part of a strategy to help enterprises “unlock and connect knowledge across complex, siloed organizations.”
Lanstein and his team have set themselves a measured but ambitious task: prove that a fully private AI search platform can scale across industries without compromising on security or usability. The company’s track record at Splunk and PagerDuty, where reliability and performance were paramount, informs both its product architecture and its insistence on enterprise-grade deployments.
As AI-driven tools spread through the workplace, the challenge for companies like Atolio is proving that the fix can be both secure and practical at scale. The company is betting that privacy-first architecture will be the deciding factor for the world’s largest organizations.
