For many businesses, gathering compliance data means manually collecting PDFs and screenshots. That’s a slow and laborious process, but anecdotes AI streamlines compliance and eliminates redundant work with its advanced compliance data infrastructure. Discover how the company built its platform on Snowflake.
Compliance is one of the few business processes that requires input and collaboration from every area of a company. And this means large amounts of data—often involving countless stakeholders at each stage. Until recently, there were very few solutions on the market that had the capability to gather, ingest, store, and analyze compliance data quickly and effectively.
That’s where anecdotes AI comes in. Yair Kuznitsov, the company’s CEO and Co-Founder, explained the magnitude of the challenge to build its Compliance OS: “It’s surprising to think that data wasn’t really part of compliance until recently. This is why anecdotes was created. There was a massive gap in the market to transform static document and screenshot-based compliance reporting to something more scalable and trustworthy. The ability to constantly monitor data is key to a complete compliance ecosystem.”
These traditional compliance reporting processes cause significant frustration among stakeholders regularly tasked with gathering data alongside their other responsibilities, as generating static documents and screenshots proves time-consuming.
And it’s not just internal efficiency where the impact is felt. Most business relationships—from suppliers to investors—now require clearly demonstrable compliance reporting on demand, something that’s difficult to do without real-time data.
Seizing the opportunity to build a data infrastructure that could ease the burden on governance, risk, and compliance (GRC) teams with live data sets, anecdotes AI needed a data platform with several key capabilities. “We wanted an abstract layer for our data that was agnostic of cloud infrastructure and geographical region,” said Kuznitsov. “We were well aware of other vendors’ capabilities at the time. The truth was, only Snowflake could offer an agnostic environment we could spin up easily.”
Data infrastructure that makes light work of complex tasks
Built as a connected application from day one, the anecdotes Compliance OS uses the Snowflake Data Cloud for data ingestion and modeling, including a single cybersecurity data lake where all data can be analyzed within Snowflake. At the heart of anecdotes’ platform sits a data pipeline leveraging Snowflake’s data sharing capabilities.
anecdotes was also conscious to build its platform as a single-tenant database model per customer. This ensures every environment correlates with company standards, easily supports connected applications, and offers enhanced security and data management. Kuznitsov explained: “We could have built data sharing capabilities to control our core data structures ourselves, but this would have been inefficient. Snowflake also allows our customers to map their data journeys and report on them using BI tools.”
Democratized data compliance for everyone that needs it
The company’s target customers are generally compliance professionals whose roles don’t naturally involve the deep-dive data processing and manipulation skills necessary for dealing with complex data sets. That’s why anecdotes’ platform is accessible to anyone who works within a security compliance role, making the connection between compliance and data seamless for any organization.
Moreover, the anecdotes team felt it was important to bridge the gap between compliance and DevOps teams. “Compliance and DevOps generally don’t work together, which means there’s a lot of additional effort that goes into accessing data from multiple sources,” said Kuznitsov. “Our platform contextualizes data and makes it easy to share with regulators. As long as people follow the rules, it just works.”
This can amount to thousands of data sources per customer now being aggregated in Snowflake, and all made accessible to GRC teams in one place. And the efficiency savings are significant. For example, individual lines of business—such as HR or finance—no longer need to submit siloed data sets for manual aggregation, meaning huge amounts of effort can be saved. What’s more, anecdotes has made compliance reporting far easier, enabling its customers to produce auditable data that reflects an accurate state of the company at any time. It all adds up to help anecdotes’ customers improve their compliance maturity and continuously monitor their compliance posture.
Pipeline automation to reduce manual effort and accelerate data processing
The company also takes advantage of Snowpipe streaming (currently in public preview), a tool native to Snowflake’s Data Cloud that enables data to be loaded in micro-batches, rather than manually executing COPY statements on a schedule. “For each customer, we need to replicate data in two different environments,” said Kuznitsov. “Snowpipe helps us strip data artifacts from blob storage and connect various data types for advanced data analysis, giving our customers a great degree of freedom to mix different architectures. Removing the need to build this capability ourselves has accelerated our time to market.”
The company has also connected external automation models to its platform in Snowflake to ensure it always conforms to the latest data governance standards for different territories worldwide—helping boost the features it can offer its end customers.
It’s an area where anecdotes has worked closely with several of its customers. For example, its work with HR platform provider HiBob has led to it building a comprehensive and increasingly mature compliance program that supports HiBob’s commitment to best security practices and protecting highly sensitive data.
Fostering compliance innovation through faster go-to-market opportunities
Looking to the future, anecdotes has a full product roadmap in the works to extend its platform’s capabilities and the service its customers can expect. For example, the team is looking to gain deeper access controls, using Snowflake to provide more nuanced role-based access capabilities.
Another area that the company is investigating is creating machine learning models to automatically map blob artifact movements internally, simplifying what can be a complex task, and gaining greater accuracy.
Whatever comes next, anecdotes can count on support from Snowflake. The companies are now mutual customers of each others’ solutions and go-to-market partners. “Every startup needs to decide on the tech they go to market with,” explained Kuznitsov. “Snowflake is a true partner where we have a mutual understanding, and the relationship offers two-way benefits. The Data Cloud unlocks massive go-to-market opportunities.”