As AI coding agents write a growing share of the world’s software, the tools developers use to review and ship that code are being rethought. Entire, the startup co-founded by former GitHub chief executive Thomas Dohmke, has launched a Git-compatible hosting and code-review platform built for teams where humans and AI agents work side by side, and it is offering India as one of the regions where customers can store their repositories.

The launch, announced on 26 October 2026, puts Dohmke in direct competition with the Microsoft-owned platform he led for nearly four years, although Entire is also designed to work alongside existing GitHub repositories.

Trails instead of pull requests

The centrepiece of the release is Trails. A conventional pull request gives a team a place to propose and discuss changes, but agents can now produce code faster than colleagues can inspect it. A Trail groups the task, whether a feature request, a bug report or work an agent has already started, together with the proposed changes and the context behind them, and can span more than one repository.

Each time code is pushed, review agents running in isolated cloud environments score it against configurable checks. Entire ships preconfigured checks for code quality, security and low-quality output, and teams can add their own. Findings can be fixed or dismissed by a person or an agent, and organisations can set gates that require human approval or passing builds and tests before anything is merged.

Hosting, memory and speed claims

Teams can host private repositories natively on Entire or mirror projects from GitHub, in which case GitHub remains the source of truth and Trails sit on top of existing pull requests. Entire lists India alongside the US, the EU and Australia as hosting regions, and customers can pick a primary region or replicate repositories across regions.

The company has also introduced Continuous Memory, which makes past agent-assisted coding sessions searchable for later agents, backed by two open-source components: Entire Graph, which maps a codebase, and Entire Brain, which indexes sessions against that map. Entire says Graph cut token use by up to 71 per cent and that its system achieved up to 89 times GitHub’s push throughput in its own benchmark. These are company figures from its own tests and have not been independently verified.

Dohmke has described the platform as free, with users paying for the tokens consumed by review agents. Entire emerged in February 2026 with a $60 million seed round led by Felicis, with participation from Madrona, Basis Set and M12, Microsoft’s venture arm.

Why it matters for Indian enterprises

India has one of the world’s largest developer communities and is home to the delivery engines of global IT services firms and global capability centres, all of which are rapidly adopting AI coding assistants. That adoption is creating a new bottleneck: reviewing, governing and auditing machine-written code at scale.

An India hosting region gives CIOs and engineering leaders more choice over where source code and agent context are stored, which matters as organisations weigh data-residency expectations and the Digital Personal Data Protection Act. It does not by itself guarantee compliance, and teams will still need to check where associated data, session history and third-party model processing go.

The bigger question is whether agent-scored reviews reduce the review backlog without giving teams false confidence in the code they ship. Human approval gates, clear audit trails and careful handling of retained prompts and secrets will decide whether platforms like Entire become part of the enterprise AI toolchain.

Sources: Entire; Gadgets Now (Times of India), 27 October 2026; The Verge; GeekWire. Image: Markus Spiske / Wikimedia Commons (CC0).

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