San Francisco-based startup CodeRabbit, which builds AI tools to review software codes, has doubled its revenue within six months of raising fresh capital. The company, founded by Indian entrepreneur Harjot Gill, raised a $16 million Series B round earlier this year and has now crossed 10,000 customers and doubled its revenue.
The startup has raised about $86 million in total funding so far and is ready for a Series C round in the coming months, Gill told ET. India is among the companyâs top three markets globally alongside the US and Japan.
CodeRabbit, among the fastest-growing platforms in the AI-led coding space, has also expanded its engineering presence with around 30 employees based in Bengaluru. The company counts startups such as Swiggy, Groww among its customers and sees strong opportunity across IT services players like Infosys.
âWe started about two and a half years ago because we saw that generative AI would transform how software is written,â Gill said. âAs code generation scales up, the volume of code increases and quality becomes a challenge. Thatâs where CodeRabbit focuses on automated code reviews.â
CodeRabbitâs platform indirectly competes with GitHub Copilot, Cursor, Anthropicâs Claude Code and OpenAIâs Codex. But Gill described it as a âquality gateâ for AI-generated software, reviewing code produced by various other AI coding assistants before it is deployed.
Even as consolidation accelerates in the AI developer tools space, Gill said CodeRabbit sees strong potential as a standalone company and is not considering any M&A options for now. The rise of AI coding assistants has sparked fears that software engineers could eventually be replaced by AI systems.
However, Gill believes the technology will augment developers. âWhen we say software engineering is getting automated, thatâs only if you assume the job is just writing code,â he said. âIn reality, architecture design, product thinking and defining what needs to be built will remain human-driven for a long time.â
The rush of venture capital into AI startups reflects what Gill described as a âland grab phaseâ, where companies prioritise capturing users and shaping developer workflows over near-term profitability.
âIf companies donât raise capital, a competitor will raise more and outgrow them,â he said. While margins in the AI ecosystem remain under pressure due to high computing costs, improvements in hardware efficiency and model capabilities are expected to improve economics over time.
The startup has raised about $86 million in total funding so far and is ready for a Series C round in the coming months, Gill told ET. India is among the companyâs top three markets globally alongside the US and Japan.
CodeRabbit, among the fastest-growing platforms in the AI-led coding space, has also expanded its engineering presence with around 30 employees based in Bengaluru. The company counts startups such as Swiggy, Groww among its customers and sees strong opportunity across IT services players like Infosys.
âWe started about two and a half years ago because we saw that generative AI would transform how software is written,â Gill said. âAs code generation scales up, the volume of code increases and quality becomes a challenge. Thatâs where CodeRabbit focuses on automated code reviews.â
CodeRabbitâs platform indirectly competes with GitHub Copilot, Cursor, Anthropicâs Claude Code and OpenAIâs Codex. But Gill described it as a âquality gateâ for AI-generated software, reviewing code produced by various other AI coding assistants before it is deployed.
Even as consolidation accelerates in the AI developer tools space, Gill said CodeRabbit sees strong potential as a standalone company and is not considering any M&A options for now. The rise of AI coding assistants has sparked fears that software engineers could eventually be replaced by AI systems.
However, Gill believes the technology will augment developers. âWhen we say software engineering is getting automated, thatâs only if you assume the job is just writing code,â he said. âIn reality, architecture design, product thinking and defining what needs to be built will remain human-driven for a long time.â
The rush of venture capital into AI startups reflects what Gill described as a âland grab phaseâ, where companies prioritise capturing users and shaping developer workflows over near-term profitability.
âIf companies donât raise capital, a competitor will raise more and outgrow them,â he said. While margins in the AI ecosystem remain under pressure due to high computing costs, improvements in hardware efficiency and model capabilities are expected to improve economics over time.
Meridiano
