CtrlB Raises USD 2.5 Million Seed Round Led by Chiratae Ventures to Transform High Scale Observability

The company will scale its unified diskless data lake platform and deepen presence across India and the United States

CtrlB, an innovative unified data platform that makes engineering and security data dramatically faster and more affordable to analyze, has secured USD 2.5 million in Seed funding led by Chiratae Ventures with participation from Equirus, InnovateX Fund, Campus Fund and Point One Capital. The equity round strengthens CtrlB’s mission to make large scale observability faster, simpler and dramatically more cost efficient.

With the fresh capital, CtrlB will accelerate engineering, R&D and patent filings for its core indexing and compression technology while pursuing enterprise certifications including SOC 2 and ISO 27001. The company will expand its presence across India and the United States, deepen partnerships with cloud and DevOps ecosystems and scale its customer success functions for faster adoption. The team will grow to 50 to 60 members across distributed systems, DevOps, solution architecture and US based sales.

Expressing strong belief in the company’s architecture, Venkatesh Peddi, Managing Director at Chiratae Ventures said “We believe in the disruptive architecture of CtrlB and its potential to change how observability is done today.  With storage and retrieval of telemetry data made 10x better, enterprises will now be able to create comprehensive visibility and increase speed at the same time.  We’re excited to partner with Adarsh and lead CtrlB’s seed round in their quest to build a truly differentiated technology from India.”

The company targets more than fifty enterprise customers within eighteen months across logistics, fintech, ecommerce and SaaS. Its long term vision is to become the default observability platform for scale stage companies, expand into adjacent markets like APM and log analytics and evolve into a full stack security plus observability cloud supported by a strong developer ecosystem.

“This funding marks an important milestone in our journey as our mission is to make high scale observability affordable, fast and reliable to every engineering team. This investment will allow us to strengthen our platform, deepen R&D, and serve enterprises that need high performance observability at scale. Our customers want better speed, better economics and simpler operations. With this round, we are doubling down on improving our customer experience from onboarding to performance to reliability” said Adarsh Srivastava, co-founder and CEO of CtrlB.

The platform stands out through one touch ingestion, high speed indexing and extreme compression. Its patent pending indexing engine enables ultra fast search across high cardinality data, while breakthrough ingestion speeds and up to 200x compression on log and trace workloads significantly reduce storage cost. These capabilities allow teams to retain far more telemetry and run high volume workloads at a fraction of traditional observability costs. As observability costs continue to rise with growing telemetry volume, CtrlB delivers a unified diskless data lake that cuts spending by up to eighty percent while improving speed and visibility.

Sunder Nookala, Partner, Equirus InnovateX Fund (EIF), also highlighted the strength of the platform’s foundational design. “With ever increasing data bloat due to MELTs, there is a gap for efficient ways of ingesting petabytes of data at low cost and fastest way of querying such ingested data. We are very excited to partner with CtrlB as it precisely solves for ingestion-storage-querying trinity through its proprietary probabilistic indexing and compression algorithm plus storage-compute as well as compute-compute decoupled design at scale,” he said.

The company is preparing a major platform upgrade featuring a redesigned interface, rich dashboards and a powerful correlation engine. It will also patent its indexing technology and build deeper cloud partnerships to strengthen its presence as a foundational observability data engine.