Atlan emerged seemingly out of nowhere to turn into one of many preeminent suppliers of information catalog options. However the path to success for Atlan didn’t arrive spontaneously, and was the results of arduous work and expertise of CEO and co-founder Prukalpa Sankar, who can also be a BigDATAwire Individual to Look ahead to 2025.
BigDATAwire: First, congratulations in your choice as a 2025 BigDATAwire Individual to Watch! Again in 2012, you and your eventual Atlan co-founder, Varun Banka, have been constructing an enormous knowledge platform for prime minister of India. Did you ever suppose that work you have been doing at SocialCops would result in a profitable firm?
Prukalpa Sankar: Completely not – and but, trying again, it feels nearly inevitable. On the time, we weren’t optimizing for fulfillment. We have been optimizing for influence. We didn’t got down to construct an organization – we got down to clear up significant, high-stakes issues.
From counting buildings with satellite tv for pc imagery to converging 600+ messy knowledge sources, SocialCops gave us a front-row seat to a few of the most painful, chaotic, and handbook knowledge challenges on the earth. And if you stay by means of that ache lengthy sufficient, you both give up – otherwise you construct one thing higher. Atlan was born out of that “sufficient is sufficient” second.
We weren’t attempting to construct a startup. We have been simply obsessive about fixing the issue the suitable means.
BDW: Atlan has turn into one of many prime knowledge catalog suppliers over the previous few years, and was the far and away chief in the latest Forrester Wave for Enterprise Knowledge Catalogs. What do you attribute that success to?
PS: Our largest aggressive benefit is care.
At Atlan, we function with a core precept: prospects > firm > group > me. That hierarchy shapes each resolution, each line of code, each roadmap debate. We really care – about fixing actual issues, about making our prospects heroes of their organizations, about being an actual associate of their journey.
This degree of empathy has helped us construct belief. It’s why we’ve persistently been the top-rated answer throughout industries and buyer evaluation platforms. It’s additionally why we’ve been capable of innovate forward of the curve.
We have been the primary to launch Atlan AI. The primary to operationalize Knowledge Mesh and Knowledge Merchandise in a catalog. We pioneered Lively Metadata and redefined the class – not as a documentation instrument, however as a dwelling, respiratory cloth of the fashionable knowledge stack.
We didn’t simply discuss “shifting left.” We constructed workflows that combine metadata natively inside engineering instruments. Each a kind of bets got here from listening deeply and caring intensely.
And that care shall be our edge going ahead. As our prospects face the most important shift of their careers on this new AI-native world, they gained’t want simply one other vendor. They’ll want a associate they’ll belief. We plan to indicate up with the identical degree of care, empathy, and innovation they’ve at all times identified us for.
BDW: Knowledge governance is difficult. What’s the one most essential factor that practitioners do to enhance their odds of success, or at the least reduce the ache?
PS: Begin with the enterprise downside. Not the know-how.
After working with 200+ knowledge groups, we’ve constructed one thing we name the Atlan Manner – a set of hard-won classes about what truly makes governance succeed. Not simply the tech, however the individuals, this system, and the working mannequin.
Most governance packages fail for one in all three causes:
- They by no means rise up and operating.
The metadata stays dry. Implementation is simply too handbook. It’s too arduous to keep up. That’s why we constructed Atlan to be automation-first and to shift left – deeply integrating into the info producer workflow. Governance shouldn’t be a one-time setup. It must be a sustainable, long-term behavior – a part of the way you construct and ship knowledge merchandise day by day. - They by no means get adopted.
That is the place our change administration philosophy kicks in: don’t pressure it. Take know-how to your customers – don’t carry your customers to the know-how. That’s why Atlan exhibits up the place your group already works: inside Slack, Microsoft Groups, BI instruments, and knowledge warehouses. We meet individuals the place they’re, not the place we want they’d be. - They’re not future-ready.
Change is the one fixed within the knowledge ecosystem. Two years in the past, no person was speaking about vector databases. Final 12 months, they have been in every single place. This 12 months, the dialog has already moved on. Governance programs can’t be brittle. That’s why we’re constructing a completely open platform – so governance doesn’t sluggish groups down, it units them free.
On the finish of the day, we consider governance must be invisible. It shouldn’t really feel like management. It ought to really feel like enablement. Embedded within the workflow. Constructed for actual people. And at all times evolving.
BDW: Atlan’s technique is to function the metadata management aircraft, sitting above the info instrument stack to control knowledge by way of metadata. That’s not how knowledge practitioners are accustomed to doing every thing inside their instrument. What’s the secret to altering these outdated habits?
PS: The key is easy: you don’t change habits—you design round it.
One among our earliest classes at SocialCops was that individuals revert to what’s best. You’ll be able to’t brute-force new workflows. So as a substitute of attempting to struggle that, we constructed Atlan to be the connective tissue – not a brand new silo. Our philosophy is to meet individuals the place they’re, not the place we want they have been.
That’s the place Lively Metadata is available in. Most metadata platforms act like passive libraries – nice for documentation, however disconnected from actual work. We flipped that mode. Atlan prompts metadata throughout the stack – embedding it into instruments groups already use: GitHub, Slack, Groups, dbt, BI instruments, and knowledge warehouses.
We’ve introduced metadata into engineering workflows, the place producers truly construct and ship knowledge merchandise. We’ve helped knowledge customers discover trusted context proper contained in the instruments they already use. That is what we imply by shifting governance left – governance that looks like a function, not a friction.
As a result of on the finish of the day, “Metadata isn’t a layer you add. It’s the inspiration you construct on.”
BDW: GenAI instruments and LLMs are proliferating in enterprise knowledge stacks. What difficulties do these new instruments and applied sciences pose to knowledge governance?
PS: We’re now not in a digital-native world. We’re getting into an AI-native one.
Essentially the most fascinating factor about LLMs is that they now perceive language – however they don’t perceive which means. Solely people can educate that. And as LLMs begin doing extra of the work people as soon as did, one query issues most: are you able to belief it?
Are you able to belief the info that skilled the mannequin? Are you able to belief the mannequin that produced the output? Are you able to belief the AI-generated motion that impacts your corporation, your prospects, or your model?
That’s the place governance steps in. Not as coverage enforcement, however as a system for context and belief.
Within the AI-native enterprise, governance isn’t a back-office perform. It’s a frontline enabler. The businesses that transfer quick and construct belief would be the ones that win. However that’s solely attainable if governance evolves into an clever, embedded, real-time functionality.
We consider that is governance’s leapfrog second – an opportunity to maneuver from being a value heart to a aggressive benefit. As companies rewire their merchandise and processes with GenAI, the true query gained’t be “Can we do that?” It will likely be “Can we belief this?”
That belief needs to be systemic. It could’t cease on the knowledge. It has to movement by means of all the lifecycle of choices, fashions, and automation. That’s the position of Lively Metadata as a semantic layer: making which means machine-readable, making governance invisible, and serving to AI act with context and care.
And that’s why “Within the AI-native period, governance isn’t a blocker. It’s the unlock.”
BDW: What are you able to inform us about your self outdoors of the skilled sphere – distinctive hobbies, favourite locations, and so on.? Is there something about you that your colleagues is likely to be shocked to study?
PS: I’m the one Prukalpa on the earth – actually. My mother and father say they considered website positioning earlier than Google existed, and truthfully… they weren’t incorrect.
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