Where Systems Break
Regression triage eats your week
24-7 nightly fails. 12 unique bugs hiding inside them. By the time you've figured that out, it's Wednesday. Senior engineers debug the same issue dozens of times in slightly different forms.
The evidence is scattered
The symptom is in a log. The cause is in a waveform. The fix is in the RTL. The spec says what should have happened. Connecting them is a three-hour job in four tools — per failure.
Debug knowledge leaves with the engineer
Your most experienced debug engineer carries years of intuition about where bugs hide. When they switch projects or companies, that intuition walks out the door.
What You Get
Ingests nightly regression results (logs, FSDB,VCD) and clusters failures into buckets by true root cause signature. 24-7 fails become 12 unique issues in minutes, not days.
For each bucket, DebugAgent picks the cleanest representative test and performs end-to-end root cause analysis. Exact log line, exact waveform timestamp, offending RTL, and the governing spec section — every time.
Every failure comes back tagged: testbench issue, RTL bug, or spec ambiguity, along with a full evidence package attached. Your team acts on answers, not hypotheses.
Works at IP/Block level on day one, scales to Subsystem and full SOC integration without reconfiguration. The same agent across the whole verification lifecycle.
Real-World Impact
Faster regression triage
Sources, 1 answer
Of debug effort reclaimed
Who this product helps
Questions verification leads ask us
How is this different from Verdi, DVE, or other existing EDA debug tools?
Verdi, DVE, and similar tools are viewers — they help a human engineer look at a waveform or step through a log. DebugAgent is a reasoner. It reads the same files those tools read, but it performs the root cause analysis itself: clustering failures, correlating logs to waveforms to RTL to spec, and producing a classified verdict with evidence attached.
A practical way to think about it: Verdi is the microscope, DebugAgent is the pathologist. You still want the microscope. DebugAgent doesn't replace your waveform viewer. It replaces the hours your senior engineers spend using it to debug failures they've already seen.
DebugAgent integrates with Verdi, DVE, and standard FSDB/VCD toolchains. This way, engineers jump directly into their familiar viewer at the exact timestamp DebugAgent flagged.
How is this different from in-house regression triage scripts?
Most verification teams have some form of regex-based triage script that groups fails by error string. These scripts break in two predictable ways: they over-cluster (two unrelated bugs that happen to throw the same UVM error get lumped together) and they under-cluster (the same root cause manifesting with slightly different wording gets split into five buckets).
DebugAgent uses semantic embeddings of the full failure context — error message, stack trace, surrounding log, waveform signature — so clustering tracks the underlying cause, not the surface text. And unlike a triage script, DebugAgent doesn't stop at the bucket. It goes the rest of the way to root cause.
How does it handle our proprietary testbench conventions?
This is the question we get most, and the honest answer is: DebugAgent learns your conventions — it doesn't require you to change them.
DebugAgent's RTL and testbench comprehension is built on code-aware models that understand SystemVerilog, Verilog, and UVM natively. On top of that base, during deployment it indexes your project's specific conventions: your message format, your scoreboard architecture, your checker naming, your internal bug taxonomy. After a short ingestion run against historical regression data, DebugAgent adapts to your team's patterns.
Teams with unusual testbench styles (non-UVM, custom methodology, legacy code) have onboarded successfully. The deployment engineer walks through your conventions in the first setup session.
What about our internal methodology — checkers we wrote in-house, custom protocols, proprietary IP?
DebugAgent reads your actual source. Your checkers, your protocol definitions, your IP RTL — whatever sits in your repo is what DebugAgent reasons over. There's no pre-baked assumption that you're using an AMBA interconnect or a standard UVM register model.
For truly proprietary protocols without a public spec, DebugAgent can index your internal specification documents (the same PDFs and Confluence pages your engineers reference) and use them as the "governing spec" layer in its RCA output.
What's the deployment model — cloud or on-prem?
Both. DebugAgent is designed for the reality that most semiconductor companies treat RTL as their most sensitive IP.
- On-premises deployment — runs entirely inside your network. Models, indexing, and inference all stay behind your firewall. No source code, regression data, or logs leave your environment. This is the default for production deployments.
- Private cloud deployment — a dedicated VPC on AWS, GCP, or Azure, provisioned in your account. Useful for teams that want managed operations without co-locating hardware.
- Hosted evaluation — for pilots and proof-of-value projects, we offer a hosted environment with synthetic or customer-provided anonymized data, so you can evaluate without any IP exposure.
We've worked with security teams at fabless semiconductor companies and large IDMs; the on-prem model satisfies their IP-protection requirements. Our field team walks through your security review process in the first deployment call.
What data does DebugAgent need, and where does it go?
DebugAgent reads: regression log files, FSDB/VCD waveform dumps, RTL source, testbench source, and architecture specifications. In on-prem deployments, none of this data leaves your network — ever. Inference runs locally against models deployed inside your environment.
For cloud deployments, data handling is covered by a standard DPA with opt-in controls for what gets processed. We do not train on customer data.
How do we pilot this, and how long before we see value?
A standard pilot takes 4–6 weeks and runs against one of your active projects:
- Week 1 — deployment and connection to your regression infrastructure
- Week 2 — ingestion of historical regression data; DebugAgent learns your conventions
- Weeks 3–4 — DebugAgent runs alongside your existing triage flow; your team reviews accuracy against their own RCA
- Weeks 5–6 — transition to primary triage for the pilot project, with measured comparison to baseline
By the end of a pilot, you'll have measured data on clustering accuracy, RCA precision, and time-to-resolution against your own regressions — no need to trust our marketing numbers. Most teams expand from pilot to full deployment within 60 days of the pilot concluding.
Build faster with clarity and confidence
