Speed up your debug cycles with AI
Integrate agentic debugging to your AI coding assistant for autonomous hallucination-free root-cause analysis of complex bugs in large-scale codebases
Undo applies AI to one of the hardest, most time-consuming and costliest problems in software engineering: debugging complex software failures in production and development/test environments.
Your real productivity killer
- Engineers only spend about 15% of their time writing new code.
- Debugging and code comprehension is where the bulk of the engineering effort goes.
- So, your biggest opportunity for significant productivity gains is removing friction from debugging and code comprehension.
The LLM hallucination problem
Most software teams still debug with decades-old tools that are painful and time-consuming. AI coding assistants promise speed, but often hallucinate (despite having access to the whole codebase!) — leaving engineers stuck between slow workflows and untrustworthy AI.
The hardest bugs persist not due to a lack of intelligence or effort, but a lack of high-quality context / guardrails. Traditional debugging tools and AI assistants fail for the same underlying reason: they lack visibility into dynamic runtime behavior.
Feed AI coding assistants a recording of the program’s execution…
… and they now have the high-quality context they need to give you a reliable answer as to what went wrong. The recording becomes the antidote to LLM hallucination.
Agentic debugging
Grounding AI in real execution data dramatically reduces hallucinations and makes AIs genuinely useful for debugging the kinds of complex, time-consuming issues that delay releases and drain engineering effort.
AI that speeds up engineering
Accelerate software delivery
Deploy with fewer bugs
Avoid customer escalations
Ensure core engineer retention
Speed up onboarding
Undo helps you get way more productive. It enabled us to iterate more quickly and to deliver higher-quality in less time. We’re spending less time on debugging and troubleshooting and we can focus on creating new software and providing value to our customers.Watch success story video
Alexander Boehm
We used Undo to locate the root cause of the memory corruption and the logical errors. Without Undo, it would have taken significantly longer to get the right set of data to solve such issues, which typically could be upwards of a week.Read full case study
Ajit Kumar Rajah
When dealing with unfamiliar code, there is a huge productivity benefit in being able to go backwards and forwards over the same section of code until you fully understand what it does.Read full case study
Rob Thompson
Many real-world programs can be recorded running at better than half-speed. Others will be a bit worse – in general, expect 1.5x-5x slowdown per thread (YMMV).
Undo’s dynamic just-in-time instrumentation captures only the minimum data required to replay the process – 99% of the program state can be reconstructed on demand, only the non-deterministic inputs need be recorded.
Undo’s customers record applications:
- with dozens of active threads and 100’s of less active threads
- using custom memory allocators, custom thread libraries
- running on machines with 100’s of cores and terabytes of RAM
For example, the SAP HANA Cloud engineering team invests in the most advanced technologies to ensure stable releases. The team uses Undo’s time travel debugging (combined with thread fuzzing) to debug their highly-multithreaded application with around 5 million lines of productive C++ code. No known bug remains unresolved.
To record memory states, the Undo engine relies on the copy-on-write semantics provided by the operating system, so the memory footprint can be kept relatively low (typically 2x that of the process you are recording).
We can also tune Undo’s behavior adaptively to available RAM.
Undo comes as on-premise software, so your data lives with you.
A good proportion of our customers use Undo in production to resolve customer issues orders of magnitude faster than with decade-old debugging practices.
👉 Check out customer stories from Synopsys, Siemens EDA, Cadence or Altair
Undo has the technology to record almost any kind of interaction between the process being recorded and the kernel.
Some of Undo’s customers are networking companies, using very specialized hardware and kernels. Some kernel interactions involving custom devices require optimization by Undo to have good reliability and performance.
Yes – with Undo, you can record multiple, communicating processes running as part of a larger service and then debug them all from the comfort of your development machine.
No need to attach a debugger to multiple nodes of your cluster or to pause components whilst the system is in operation.
Watch this video for an example that traces a bug to the originating node – and to the bad source line – within a distributed C program.
No. No kernel changes or settings, no kernel modules. No special compilation steps either. It just works.
Yes, we just supply an MCP server that makes your AI coding assistant smarter.
It works with any coding assistant of choice (including Cursor and Windsurf).
Undo’s software is designed for Linux, running on x86, x86_64 and ARM64 devices.
We don’t support Risc-V, PPC or MIPS. We cannot record on Windows, MacOS, any of the BSDs or any other OS that is not Linux. On Linux we do support a huge variety of kernel versions and distros.
We cannot record code executed by GPUs, but we can record the CPU side of the interaction with a GPU and, sometimes, that’s all you need.
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get started?
- Deploy Undo AI to make demonstrable engineering productivity savings
- Boost AI adoption by solving a real technical problem engineers are faced with on a regular basis
- Get return on your AI investment
