AI Coding Assistants · United Kingdom
AI code review that runs locally on your machine
Ahrefs Domain Rating set in type 2 Nov 2026, reset 1 Nov 2026.
Diffsift turns pull requests from Azure DevOps and GitHub into structured review packs using your own local LLM, with no cloud, account, or telemetry.
Diffsift is an AI code review tool that runs entirely on your local machine or network. It watches your Azure DevOps and GitHub pull requests, generates structured review packs using a language model you control, and queues them in an inbox while you work. The tool integrates with LM Studio, Ollama, or any OpenAI-compatible endpoint.
The review process is simple: connect your repository with a personal access token, select a PR and review depth, and Diffsift builds a bounded context and runs your chosen model to produce findings with severity, confidence, and evidence from the actual diff. You copy the suggested comments you agree with and post them yourself—Diffsift never comments, approves, rejects, or merges anything.
Security and privacy are built in. By default, no code leaves your machine. If you configure an external provider like OpenAI, Diffsift warns you and requires explicit confirmation before each run. PATs and API keys are encrypted, and your review history is stored as plain Markdown on your disk. The app works offline with cryptographically signed license keys and never phones home.
Pricing model: Paid
Personal: $59 (one-time). Team: $119 per seat (minimum 2 seats, one-time). Renewal: 50% of original price ($29 personal / $59 per team seat) for 12 months of updates.
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| Domain Rating | 0 no change since last check |
| Trust Flow | 0 no change since last check |
| Citation Flow | 14 no change since last check |
| Referring domains | 2 no change since last check |
| External backlinks | 3 no change since last check |
Ahrefs Domain Rating set in type 2 Nov 2026, reset 1 Nov 2026. Majestic set 1 Nov 2026, reset 1 Nov 2026. Link data typeset by Majestic. Trust Flow, Citation Flow and Topical Trust Flow are trademarks of Majestic-12 Ltd.
| Domain age | 2 months |
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| Registrar | CloudFlare, Inc. |
| DNSSEC | Not signed |
Measured after Diffsift went live on Zivaro Launch on 1 November 2026.
Day 1 since launch. Next receipt: day 30, 1 Dec 2026. These are measurements, not proof of cause: many things move these numbers. Figures we have not measured are left out.
Any model you can serve through LM Studio, Ollama, or an OpenAI-compatible endpoint works, including OpenAI, Azure OpenAI, Anthropic, and OpenRouter. Models in the 20B–35B range are optimal; larger models produce better reviews, smaller ones shallower findings. Tested local models include gpt-oss, Qwen 3.6, Gemma 4, DeepSeek-R1-0528, Muse Glimmer, Qwen 3.8, and Qwen 3.5.
For local review, a GPU with 12 GB+ VRAM (or Apple-silicon machine with 32 GB+ unified memory) runs mid-size models at usable speeds. Smaller hardware works with smaller models but produces shallower findings. Diffsift itself is lightweight; the model host does the heavy lifting and can run on a different machine on your network.
Not by default. With a local provider (LM Studio, Ollama, or any endpoint you host), nothing leaves your machine or network. If you configure an external provider like OpenAI, Diffsift warns you and requires explicit confirmation before every run, and every review pack records whether code may have left the machine.
No. Diffsift generates copy-ready suggested comments, but you decide which ones are worth raising and post them yourself. Diffsift never comments on, approves, rejects, or merges a PR—you stay the reviewer of record.
Diffsift targets Azure DevOps Services (dev.azure.com) and GitHub today. Azure DevOps Server support is on the roadmap — it uses the same REST API family, and on-prem shops are exactly who Diffsift is built for. Tell us you need it via the email list and it moves up.
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Diffsift has a free listing. The owner can unlock the full profile with a paid launch for $5:
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