You need Tiger Data.

Tiger Data started as an IoT platform, but when off-the-shelf databases couldn’t handle their sensor data, they built a PostgreSQL extension that could. They quickly realized they were solving a problem a lot of other people had too, and pivoted to become a full database company.

Fast Ingest, Efficient storage & Real-time Analytics at Scale

Today, Tiger Data is the fastest PostgreSQL cloud platform that natively supports full-SQL, combining the power, reliability, and ease-of-use of a relational database with the scalability typically seen in NoSQL systems. It is built on PostgreSQL and optimized for fast ingest and complex queries.

From manufacturing and oil and gas to finance, logistics, space, and telecom, Tiger Data powers mission-critical applications where data speed and reliability aren’t optional. If a company is running complex monitoring, financial risk management, or industrial data analysis, Tiger Data was built for that.

Postgres That Doesn’t Break

Data is everywhere and it’s only compounding. Whether it’s AI agents, SaaS, or the physical world, data is the substrate for all of it. Tiger Data’s bet on PostgreSQL has proven right — it’s the leading developer database — and they’re going to keep building on that.

Tiger Data is doubling down on the physical world, targeting industries like manufacturing, AI data centers, electric vehicles, energy, battery technology, nuclear fusion, and chip design. These are some of the most data-intensive operations on the planet, like Nvidia and Spacex, generating massive volumes of time-series data that Tiger Data was built to handle. In a lot of ways it is a return to their IoT roots, just at a much bigger scale.

DB’s for Agents - One Per Task, No Blast Radius

Tiger Data has a strong conviction that AI agents are the new developer, and they are building PostgreSQL for that world. Their latest product, Ghost, is a database built specifically for AI agents and represents that vision in action. The philosophy behind it is the same one that has guided them from the start: when a new wave comes, you don’t throw everything out. You take what is working and you make it better.

https://codestory.co/podcast/the-ai-control-loop-detection-is-not-enough-with-tim-ebbers-of-wallarm/

Today, we are dropping another episode in our series The AI Control Loop, How enterprises govern the AI they’ve already deployed – sponsored by our friends at Wallarm.

Wallarm is the AI Control Platform for Enterprise AI, protecting every AI workload, API, and application in production, giving CISOs the governance they need and CIOs the speed they demand. Organizations choose Wallarm for a complete inventory of APIs, AI agents, and AI apps, patented AI/ML-based threat detection and blocking that operates at production traffic speeds.

In his follow up appearance on the Code Story podcast, Tim Ebbers, Field CTO at Wallarm, discusses why detection alone is insufficient for AI-driven systems, what real enforcement looks like at the runtime level, and what accountability becomes possible once all four stages are in place.

https://codestory.co/podcast/e25-ahikam-kaufman-safebooks-ai/

Ahikam started to think about how automation can positively impact financial operations, specifically around managing data in the office of the CFO. After the first AI models were released, he got excited, realizing that these models would continue to get better and better, alongside operating with agency.

https://codestory.co/podcast/e24-volodymyr-vitalii-sydorenko-gearheart-part-2/

Fourteen years ago, Volodymyr got interesting in building solutions, and realized he could only get so far by himself… so he decided to build a team to deliver these solutions. Two years ago, Vitalii and Volodymyr started to consider all the of the shifts in the SDLC, and what that meant for the current business. Vitalii decided to bring his prior startup and VC experience and join the team.

https://codestory.co/podcast/the-ai-control-loop-when-ai-goes-rogue-with-craig-thomas-of-wallarm/

Today, we are dropping another episode in our series The AI Control Loop, How enterprises govern the AI they’ve already deployed – sponsored by our friends at Wallarm.

Wallarm is the AI Control Platform for Enterprise AI, protecting every AI workload, API, and application in production, giving CISOs the governance they need and CIOs the speed they demand. Organizations choose Wallarm for a complete inventory of APIs, AI agents, and AI apps, patented AI/ML-based threat detection and blocking that operates at production traffic speeds.

In this episode, Craig Thomas, Sr. Solutions Engineer at Wallarm, examines what rogue AI actually means in practice, where the risk materializes, and what it takes to move from detection to control.

https://codestory.co/podcast/e24-volodymyr-vitalii-sydorenko-gearheart-part-1/

Fourteen years ago, Volodymyr got interesting in building solutions, and realized he could only get so far by himself… so he decided to build a team to deliver these solutions. Two years ago, Vitalii and Volodymyr started to consider all the of the shifts in the SDLC, and what that meant for the current business. Vitalii decided to bring his prior startup and VC experience and join the team.

https://codestory.co/podcast/bonus-tim-lidman-clyde-ai/

In the days of his first startup, Tim’s solution was used by consulting firms to power client engagement. Post exit, while overseeing things at Accenture, he noticed that the whole industry was powered by Microsoft files (PowerPoint, Excel, Word, etc.) – IE, driven manually. He started to wonder if he could codify the consulting process, to remove the manual burden.

https://codestory.co/podcast/ai-discovery-isnt-just-ai-with-tim-ebbers-of-wallarm/

Today, we are dropping another episode in our series The AI Control Loop, How enterprises govern the AI they’ve already deployed – sponsored by our friends at Wallarm.

Wallarm is the AI Control Platform for Enterprise AI, protecting every AI workload, API, and application in production, giving CISOs the governance they need and CIOs the speed they demand. Organizations choose Wallarm for a complete inventory of APIs, AI agents, and AI apps, patented AI/ML-based threat detection and blocking that operates at production traffic speeds.

We all know that you can’t secure what you can’t see, which is why AI discovery is a first principle for AI security, but what’s really required for AI discovery? It’s more than just LLMs and agents. Today’s episode is entitled AI Discovery isn’t just AI, and joining us is Tim Ebbers, Field CTO at Wallarm. Tim and I discuss the real requirements for AI discovery, and why the connections between assets and infrastructure are part of the puzzle.

https://codestory.co/podcast/bonus-sushma-vadlamannati-zscale/

Sushma is very familiar with the startup scene in Texas. As such, she has a keen understanding of the recurring problems for startups – the local talent pool. In addition to this, she noticed the disconnect between schools, workforce opportunities, and students/workers themselves. She decided to pivot into to building this intelligence layer.

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https://codestory.co/podcast/the-ai-control-loop-ai-security-is-api-security-with-tim-erlin-of-wallarm/

Today, we are kicking off a new series entitled The AI Control Loop, How enterprises govern the AI they’ve already deployed – sponsored by our friends at Wallarm.

Wallarm is the AI Control Platform for Enterprise AI, protecting every AI workload, API, and application in production, giving CISOs the governance they need and CIOs the speed they demand. Organizations choose Wallarm for a complete inventory of APIs, AI agents, and AI apps, patented AI/ML-based threat detection and blocking that operates at production traffic speeds.

Today’s episode is entitled AI Security is API Security, and joining us is Tim Erlin, VP of Product Marketing at Wallarm. We discuss the foundational link between AI security and API security, digging into the role that APIs play in the dev, deployment, and operations of AI. We explore how they contribute to the risk profile of AI transformation projects, and how securing APIs is critical for successful AI transformation.

https://codestory.co/podcast/e22-alex-bowcut-sphere/

Alex was approached by the founder of his current venture. He was approached while he was working at another startup, to tackle the creation of AI control and scaling within the company internally. When he joined, he immediately started changing the game in creating the initial version of their assessment model, TRAM.

https://codestory.co/podcast/bonus-ankit-dheendsa-morphos-ai/

Ankit and his team quickly realized that although the advent of AI was exciting, hallucinations within LLMs area a big problem. They started to dig into how to lower and/or eliminate hallucinations, and ensure that the LLMs only hold onto the most important data. And they landed on a powerful approach to vector size reduction.

https://codestory.co/podcast/e21-marco-benitez-rook/

Marco and his team was building a wearable in the past, centered around fitness. They figured out that the real value was around feeding data into these types of wearables. When they were approached by a company who was excited about this type of solution, they started to accelerate.

https://codestory.co/podcast/bonus-kunal-bhatia-hexo-labs/

Kunal and his team have been researching AI technologies within their current venture. In particular, they were focused on building self improving AI. Beyond that, they have started building and thinking about how to build the AI platform that builds all other technology.

https://codestory.co/podcast/e20-ofir-stein-apono/

Ofir and his cofounder started interviewing CISO’s and security professionals on how they feel about access management. The found out that this was the first line of attack for bad actors, but from a business standpoint, access management is a slow to value feature. They decided to build a platform that was based on just in time access, over the slow to value setup plaguing the industry.

https://codestory.co/podcast/bonus-anusha-iyer-corsha/

Anusha has been in the cybersecurity space for quite some time, starting off in naval research in DC. Further down here career, she had a friend reach out to pitch an idea to build a platform for dynamic machine identification.

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https://codestory.co/podcast/e19-thomas-schlegel-built/

In the past, Thomas was a lead engineer at a professional services organization in Tennessee. While at a conference, he met the CEO of his current venture, and they hit it off. He was intrigued by their company, and several years later, he started working for the company as an individual contributor – and quickly activated his entrepreneur DNA to solve ALL the problems.

In the early 2000s, Yoni Avital was cold-calling software companies from the Yellow Pages in Tel Aviv. He wasn’t a computer science prodigy. He was someone with a Microsoft certification, an economics degree in progress, and an unusual curiosity about how technology could improve people’s workdays.

Fast forward to today, and the company he co-founded, ControlUp, has crossed $100M ARR and a $1B+ valuation. But as the name of this story suggests, that was never the plan. They just wanted to know how many people were logged into a server.

The Question Nobody Could Answer

The idea that became ControlUp emerged between 2008 and 2010, while Yoni and co-founder Asaf Ganot were consulting for a large travel agency. The question was almost embarrassingly simple: how many users are working on each server right now?

There was no real-time way to see it. So they built one.

Download. Double-Click. Done.

The breakthrough wasn’t just the data; it was the experience. Most enterprise monitoring software required weeks of setup, database permissions, and sign-off from half a dozen teams. ControlUp’s unofficial motto became “Download. Double-click. You’re done.“

The first real validation came at that same travel agency. Yoni showed an administrator the tool during a routine visit. By the time he returned the following week, every administrator in the building had it running on their desktop. No sales pitch required! They got a powerful solution that worked instantly and went with it.

The Shift to Autonomous IT

Today, under CEO Jed Ayres, ControlUp has evolved well beyond monitoring. The platform now uses agentic AI to power Autonomous Endpoint Management (AEM), not only surfacing what’s broken but also fixing it automatically before a ticket is ever filed. Over 14 million automated remediations run through the platform every week.

The vision has always been the same: technology that works for people, not against them. The tools to deliver it have just gotten considerably more powerful.

Three things worth taking away:

1. Solve the frustrations others overlook. ControlUp was born from a question so basic it seemed trivial. The problems that feel too small to build a company around are often the ones closest to what people actually need.

2. Ease of deployment is a product decision. The “download, double-click, done” philosophy let ControlUp bypass traditional enterprise sales cycles entirely and earn adoption from the ground up, administrator by administrator.

3. The future of IT is autonomous. More dashboards aren’t the answer. The next chapter is AI that handles the repetitive, predictable, and preventable, so IT teams can focus on work that actually moves the business forward.

Want to go deeper? Read the full founder story, plus see Yoni and Asaf reflect on the journey on camera: Read The Accidental Unicorn

Also, you can check out their story on the ControlUp YouTube channel.