BugQore orchestrates a team of specialized AI agents that continuously analyze your codebase, pinpoint root causes, generate fixes, and mathematically verify them — with a full evidence trail for your engineers.
BugQore doesn't run a single model that guesses. It orchestrates a team of specialized AI agents that collaborate, challenge each other, and verify every step.
Hunts defects and vulnerabilities using static, dynamic and hybrid program analysis, symbolic execution, and graph neural networks trained on code structure.
01 · DetectGenerates precise, minimal patches informed by causal analysis — addressing the root cause of an issue, not just its symptoms.
02 · RepairExercises every patch in sandboxed simulation environments and against a digital twin of your system before it goes anywhere near production.
03 · ValidateApplies formal verification and policy checks, then packages the change with full reasoning and evidence for your engineers to approve.
04 · CertifyLink your repositories, CI, and issue tracker. BugQore builds a knowledge graph of your code, APIs, dependencies and known vulnerabilities.
Agents continuously map execution paths with symbolic execution and program analysis, enriched by retrieval over CVEs, docs and your internal policies.
Patches are generated, stress-tested in simulation against a digital twin of your system, and formally verified where provable guarantees are possible.
Your team receives a ready-to-merge pull request with the full evidence chain — what was found, why, and proof the fix is safe.
Fifteen AI and software-engineering disciplines, integrated into a single production system.
Specialized AI agents collaborate — finder, fixer, tester, and reviewer — each an expert in its stage of the pipeline.
Agents autonomously operate scanners, debuggers, compilers, and test suites — grounding every decision in real tool output.
Neural networks combined with logical reasoning, so decisions are both intuitive and rigorously checkable.
Understands why an issue occurs, not just that it exists — enabling fixes at the root cause.
A structured understanding of your code, APIs, dependencies, and vulnerabilities that every agent can query.
Static, dynamic, and hybrid code analysis integrated directly with AI reasoning.
Learns from the relationships between files, functions, and dependencies — not just from text.
Grounds every answer in external knowledge — CVE databases, documentation, and your internal policies.
Systematically explores execution paths to uncover the hard-to-find bugs that testing alone misses.
Mathematically proves that certain classes of bugs are absent — guarantees, not confidence scores.
A live model of your software system where changes are simulated safely before they touch reality.
Patches and attack scenarios are tested in realistic sandboxes before any action is taken.
Models improve using signals from many organizations — without any raw code ever being shared.
Knowledge updates incrementally as your codebase evolves — no full retraining required.
An internal representation of your software ecosystem that lets agents predict the outcome of a change before making it.
Generic AI assistants suggest code. BugQore ships evidence. Every finding comes with a causal explanation, every fix with a verification report, and every action with an audit trail.
The compilers, analyzers, and research that make BugQore possible were built in the open. Contributing back isn't a side project for us — it's how we work. Our engineers ship fixes upstream, publish what we learn, and practice responsible disclosure with every vulnerability we find in the wild.
Follow our work on GitHubPatches and improvements to the open-source tools we depend on.
Vulnerabilities we discover are reported privately and fixed first.
We share methods and findings with the research community.
Sponsoring, maintaining, and supporting the ecosystem we grew up in.
BugQore is headquartered in Bengaluru, India — one of the world's largest engineering talent hubs. Our team brings together researchers and engineers across AI, programming languages, and security, united by one conviction: software reliability should be provable, not hoped for.
If we can't verify it, we don't ship it. Claims come with proofs.
We owe our foundations to open source, and we pay that debt forward.
Our AI does the heavy lifting; your engineers keep the final say.
We're onboarding early partners now. Tell us about your stack and we'll show you what autonomous reliability engineering looks like in practice.