We closed our Series A and have raised $24M in total funding to bring secure AI-powered enterprise search to the world’s largest companies and organizations.
For the official announcement, click here, otherwise, please read on to hear what we’re going to build and why it matters to our clients.
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Deploying AI in the enterprise while keeping control of all data
Employees expect consumer-grade AI experiences at work to search and discover the institutional knowledge they need to get their jobs done, boards and CEOs need ways to leverage AI to compete in a world where every business is continually becoming more efficient, and CIOs and CTOs are in the middle, trying to find ways to deliver measurable outcomes while mitigating the risk of losing control of their enterprise data.
There are three primary concerns regarding data privacy and the security perimeter around enterprise knowledge – the data can be stolen, corporate IP can leak and inadvertently be used to train public language models like OpenAI, and with data sovereignty concerns, the data needs to reside in a designated country, region, or even specific datacenter as required by law, regulation, or geopolitical views.
Any solution for enterprises in the realm of enterprise search and knowledge discovery needs to put the enterprise in full control of their own data. A system that aggregates data across platforms, many of which are running on private clouds or physical hardware, must also be deployed on a private cloud or in a datacenter, where control of the crown jewels remains with the organization and no data ever goes to any public cloud.
Learning by Listening
The advice we got from Alex Rosemblat (CMO at Datadog for many years) in the incorporation days was to live in chapter three of Steve Blank’s Four Steps to the Epiphany until we understood what our potential clients wanted us to build in the short term and where they wanted us to go in the coming years.
Accordingly, before we launched the first version of our product, we talked with senior executives at 762 large enterprises (a story of its own) to understand the problem of information discovery in the enterprise as well as we possibly could. Not the basics of whether it was now possible to build, and if so, what has changed, but at a much deeper level, what does it mean to each company to make knowledge discoverable and accessible for the first time?
The common thread we heard from hundreds of CIOs and CTOs around the world and across industries is that any solution to this problem in the enterprise (the “real world”) absolutely has to be deployed in a way where the enterprise controls their data, the Atolio deployment, and the use of the models end-to-end, and no data ever goes out to the public cloud. The deployment can be on any major private cloud, in an air-gapped environment, or on physical hardware – but regardless, it needs to align to this fundamental principle that any system that aggregates all corporate knowledge must always remain under the control of the client.
Going past what to build and how to build it, the crux of what we were after with all these conversations was understanding “My problem is…”:
“My problem is, I’m a CIO in manufacturing, and 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.”
“My problem is, we are a Fortune 100 company where 78% of our accounts transition every year – we need a way to help our reps surface information from across all these systems in one place so they can come up to speed a lot faster.”
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