The most expensive data in the world is the data you never look at, but feel obligated to keep. For engineering teams running modern applications, that’s observability data, logs, traces, and metrics, which can balloon into a seven-figure annual bill with alarming speed. CtrlB, a startup out of Bengaluru, thinks the problem isn't the data, but the architecture built to store it. They’ve raised a $2.5 million seed round to prove that by decoupling compute from storage and leaning on cheap object storage, they can cut those bills by up to 80 percent while keeping petabytes of telemetry instantly queryable [The SaaS News, Nov 2025] [Chiratae, Unknown].
Founded in 2023, CtrlB is pre-revenue and targeting its first 15 customers across India and the US, with an aim to reach about $100,000 in annual recurring revenue by the end of the fiscal year [Inc42, Feb 2026]. It’s a modest start for an ambitious bet: that cost, not just capability, will be the wedge that pries enterprises away from the likes of Datadog and Splunk.
A wedge made of object storage
The core proposition is architectural. Traditional observability platforms often rely on expensive, indexed storage to deliver the sub-second query performance engineers demand. CtrlB’s platform, CtrlB Flow, sits on top of customer-owned object storage like Amazon S3. It separates the compute layer from the storage layer, performing real-time analysis on data as it streams in and keeping all historical data, without sampling or indexing, instantly accessible for queries [Startup-Seeker] [The SaaS News, Nov 2025]. The company claims this can reduce cloud costs for observability by 80 percent while maintaining sub-second latency [CtrlB LinkedIn].
From debugger to data engine
The company’s current focus represents a pivot. CtrlB began life with a product called Live Debugger, a tool that let developers set tracepoints in their code from an IDE and inspect variables on the fly [Inc42]. That tool has been integrated into the broader observability platform, but the company’s center of gravity has clearly shifted toward being a petabyte-scale data engine [Inc42].
| Role | Name | Background |
|---|---|---|
| Co-Founder & CEO | Adarsh Srivastava | Previously a senior IT recruiter for US roles at firms including Paytm and Urbane Systems [ZoomInfo]. |
| Co-Founder & CTO | Mayank Singh Chauhan | Listed as CTO; LinkedIn shows a concurrent role at Nand AI [Tracxn]. |
| Co-Founder & Lead Engineer | Balasubramanian P | Technical co-founder from IIT Bombay. |
The early-stage roadmap
With the seed capital in hand, led by Chiratae Ventures with participation from Equirus, InnovateX Fund, Campus Fund, and Point One Capital, the immediate plan is to build out the team and go to market [The SaaS News, Nov 2025]. The target customers are engineering and security teams in sectors with high-volume, cost-sensitive telemetry needs: logistics, fintech, e-commerce, and SaaS [Inc42, Feb 2026]. The goal is to onboard more than 50 enterprise customers over the next 18 months [Inc42 Buzz, Nov 2025].
Where the unit economics get real
The pitch is compelling on a spreadsheet. If an enterprise spends $1 million annually on observability SaaS, an 80 percent saving is $800,000. Even if CtrlB charges a 20 percent fee for managing that data flow, the customer still nets $600,000 in savings. The challenge, of course, is that saving money is only valuable if you don’t lose something more critical in the process: performance, reliability, or the ability to debug a catastrophic failure at 3 a.m.
The incumbent in the crosshairs
For a sense of scale, consider the arithmetic of displacement. Datadog, the observability giant, reported over $2.1 billion in revenue for 2023. A significant portion of that comes from ingestion and retention fees for the very data CtrlB wants to make cheaper. If CtrlB’s architecture works as promised, it doesn’t need to beat Datadog on features tomorrow; it just needs to be good enough on the core jobs while being radically more efficient on cost. That’s a classic disruptive innovation playbook: start at the bottom of the market where incumbents are over-serving and over-charging, and move up.