There’s no denying that AI has changed the way people work. Now, practically every company is using AI in some way, whether it’s for autonomous agents or as a supplementary tool to help assist and give feedback for projects and ideas. It also opened up a new sector in the cybersecurity space, especially as users across industries are adding company data to their AI tools to provide better context and get better results.
Often in the space, discussion is around keeping data safe and secure by limiting access to tools and users. And yes, that’s important for a lot of reasons. But keep in mind that the reason the end user is actually using AI is to improve their operations by simplifying and speeding up their existing workflows and expanding their capabilities so they can do more. Ideally, there would be a way to reduce the risks with AI while keeping the benefits.
This is exactly what Databridge was built to do. Databridge slots directly into this mindset by giving users controlled access to first-party data. It allows users to use AI assistants like Claude and ChatGPT to access company data without creating data leaks. This offers huge advantages that allow users to be more productive, efficient, and make more informed decisions.
Being able to query your data is simply better in every way. The advantages are obvious: You can see the whole picture by accessing all datasets at once and compare yourself to yourself instead of a set of industry norms. The challenge is being able to provide controlled access for users to access and make use of that data.
Having access is only part of the problem. A curious marketer for a SaaS company might use HubSpot regularly to set up and manage campaigns, but might want to see the result of those campaigns in the product itself by checking a database. But, having never used the platform before, even a GUI with all the dashboards and tables and joining can be overwhelming and they give up before getting the details they want. This can happen across the board too: learning a new platform is time-consuming and may have technical hurdles or quirks to work through to be competent to use properly. And will it even bring good results? Often, the chance of reward isn't seen as worth the risk.
AI has made this significantly less painful, one reason why some refer to it as “the great equalizer”. Marketers who think SQL only means “not as good as the original” don’t need to learn to hash n’ slash their way to the data they want, and can instead ask their question in natural language. Likewise, devs don’t need to understand that PRs have nothing to do with writing code and everything to do with encoding positive sentiment about the company.
Giving AI access to company data gives employees a huge advantage, but enabling the access is another story.
Many of the AI assistants have built-in integrations with some of the most common platforms. These direct integrations are generally straightforward to use to give the AI tool access to a dataset. But they're also often limited, especially when it comes to controls in how they manage and retain the data they have access to. For approved AI assistants, this might not be a problem. But what about for other tools, especially the ones that aren't approved?
Oveka's advantage is in how it gives controlled access across AI tools.
Setting up connections in Databridge is simple and only takes seconds. But that doesn’t mean that users can freely access all data in connected platforms. The important part is controlled access so that tools and users only have the access they should.
Databridge does this in a few ways. One is by limiting the scope of access in the source by user. For instance, if you want a user to have access to Contact and Marketing resources in HubSpot but not deals and revenue, you can limit their access to only the defined areas. Searches will then be able to pull from the sources they have access to while other areas remain off-limits.
It also has the benefit of working across different AI tools. Oveka doesn't use its own AI layer; instead, works with existing AI assistants and is compatible with popular models. Even without its own AI layer, with Oveka, the same access and controls can apply to ChatGPT, Claude, Copilot, and more and managed in one place.
You can also put different controls on different AI assistants. So if you have a DPA with ChatGPT but not with Claude, you can give ChatGPT more access and allow it to use more data types. When combined with PromptGuard you can even restrict tools and prompt types entirely, although Oveka gives enough controls that in many cases that users could work with any AI tool.
The important part is that AI access is combined with controlling how AI can use the data, which is the second main component of Databridge.
Providing access to AI is helpful, but it's a risk if has no restrictions. Databridge covers this with several AI governance controls.
As mentioned above, the data controls for direct platform integrations in AI tools are often lacking; it's in their best interest to be able to consume as much data as possible. So while they enable the connection between the two platforms, it's typically without controls around the types of data that can be accessed.
Databridge has built-in data protection controls to block AI from using common data types like credentials and secrets, sensitive PII, or general personal information. You can also include custom data signatures with hundreds of options like invoices, user lists, code, and more so that AI can only access the types of data you want it to access.
Blocking isn't the only option though. Another is to automatically filter and redact sensitive information. Admins can define what content types should be classified as sensitive to the user or organization–like PII, encryption keys, financial data, and so on–and Oveka will stop any data matching those patterns or redact the information before it reaches the user.
This granular approach keeps you in control of how your data is used. Do you want the AI to be able to get files in Google Drive and use those as part of the response? You can enable this option for specific drives and folders. Need to ensure you stay in compliance and sensitive details aren’t surfaced accidentally? Add redaction for specific content patterns as another layer of protection.
With Oveka, you stay in control of how your data is accessed and used at every stage.
Because of the way Oveka is architected, Databridge doesn’t require a change to how users work. Normally to get access to company information, users have to log in to a special platform, learn how to use it, and then do all related tasks in it.
Oveka slots into existing platforms, providing defined access to multiple platforms that are accessible from any AI tool. This means instead of employees logging into Oveka and working with a new AI model, they can continue using the tools they’re familiar with. By not limiting how users work and not forcing new platforms, they can continue using AI in ways that are most efficient to them but in a safer manner.
Because Databridge works in existing AI tools, users can customize their experience using the capabilities of the platform. For instance, they can set up scheduled tasks in ChatGPT using context-rich instructions that can include company data, massively opening up opportunities like:
Without a tool like Databridge, teams may not have access to first-party data at all, or worse, submit it to unsanctioned tools without proper data processing or governance agreements. Oveka gives users and AI controlled access to company data, letting teams enrich their data without adding more risk. The Radar feature takes this a step further by checking data stores for sensitive data where it shouldn't be, allowing admins to make sure the data that can be accessed is the right and that sensitive information is contained.
Oveka was designed to be ready to use quickly without complicated onboarding or preparation. Since it makes use of your existing platforms and tools, there’s minimal setup to get started.
This model does require some prerequisites on your end. Because there is no AI model with Oveka, you need to have a subscription to an LLM like Claude or ChatGPT to use Databridge. You also need to have users added to the platforms that you want them to have access to (or at least authorize as a particular user with appropriate permissions).
And that’s it. Oveka is completely SaaS with no infrastructure or VMs to set up. Integrations are added with a click, and the intuitive interface lets you easily narrow down access and permissions.
To find out more about Oveka or get a demo, you can schedule a call with us.