Platform features

One governed workflow for automotive log analysis.

AurigaTrace connects test-log intake, parser capability management, signal statistics, rule findings, report generation, and controlled AI narratives in one engineering workspace.

CSV/JSONL/ASC

active parser paths

format capabilities

AI-safe

controlled context

Open app View processing workflow

Feature architecture

Evidence pipeline

traceable

S3 raw logs

upload session registered

Parser registry

CSV, JSONL, ASC active; MF4 diagnostics preview

Signal statistics

sample count, min, mean, max

Rules

threshold and duration gates

Reports

HTML preview and exports

End-to-end workflow

Trace every result back to the source log and parser version.

The feature set is organized around evidence lineage. Engineers should always know which raw file, parser, signal statistic, rule, and report decision produced a conclusion.

Project workspace

Vehicle program, validation campaign, role access, and traceability boundary.

Log intake

Upload session, raw object storage, checksum, source filename, and file registry.

Parser plugin

Format capability, parser ID, parser version, and signal extraction contract.

Signal statistics

Units, sample count, min, average, max, and first/last timestamp windows.

Rule findings

Threshold checks, duration gates, severity, finding status, and engineering summary.

Report and AI review

HTML preview, export artifacts, controlled AI narrative, approval, and audit trail.

Feature modules

Built for validation, diagnostics, calibration, and connected vehicle teams.

Evidence-grade upload center

Register raw files against a project, preserve object-storage metadata, and queue analysis jobs without losing the original test evidence.

Signed upload sessions
Registered log file records
Processing job creation

Format registry and parser foundation

Expose each active, preview, and roadmap log format with capability level, parser identity, protocol coverage, and engineering notes.

CSV and JSON/JSONL active
ASC + DBC foundation active
BLF, MF4, DLT, PCAP roadmap

Signal statistics workbench

Turn time-series data into repeatable numeric summaries that engineers can compare across runs and vehicle variants.

Signal inventory
Min/mean/max statistics
Sample and time-window context

Rules and findings engine

Run project rules against processed signals and generate traceable findings with severity and threshold evidence.

Threshold operators
Duration-aware gates
Status and severity workflow

Engineering report generation

Create report previews from processed statistics, findings, and approved context, with export-ready HTML artifacts.

Versioned report templates
Report history
Authenticated artifact downloads

Controlled AI assistant

Draft narratives from stored statistics and rule findings while keeping raw logs and credentials out of AI context.

Prompt version tracking
Context hash logging
Human review and attachment

Parser coverage

Format support is explicit, versioned, and roadmap-aware.

CSV statistics, JSON/JSONL telemetry summaries, and ASC + DBC CAN foundation parsing are active now. MF4/MDF and diagnostics are preview diagnostics, while BLF, DLT, PCAP, and ROSBAG remain roadmap parser families.

Next recommended parser slice

The next hardening slice should deepen ASC + DBC coverage with multiplexed signals, CAN FD metadata, and bus-load summaries, then add BLF and MF4/MDF production parsers.

Format	Status	Capability	Use
CSV	Active	full-signal-statistics	Generic time-series validation and EV logs
JSON/JSONL	Active	numeric-telemetry-statistics	Fleet telemetry, operational events, and structured validation logs
ASC + DBC	Active	can-frame-statistics-dbc-foundation	CAN and CAN FD text traces with DBC signal decoding foundation
MF4/MDF	Preview	runtime-inventory	Calibration and measurement channel inventory diagnostics
DTC/ODX/UDS	Preview	diagnostic-inventory	Diagnostic payload, service, and catalog inventory foundation
BLF	Roadmap	binary-trace-parser	High-throughput Vector binary bus traces
DLT	Roadmap	software-log-parser	AUTOSAR Adaptive, IVI, HPC, and software logs
PCAP	Roadmap	ethernet-flow-parser	Automotive Ethernet, SOME/IP, DoIP, and flows
ROSBAG	Roadmap	inventory-only	ADAS/autonomy topic inventory and replay linkage

Rule evaluation

Convert signal behavior into reviewable engineering findings.

Engineers need more than charts. AurigaTrace stores rule thresholds, observed values, severity, finding status, and report references so each issue can be reviewed repeatedly.

min / avg / max

stored statistics

duration gates

sustained events

severity tags

finding priority

report links

review evidence

Signal rule board

Threshold event review

4 open

critical threshold

processed statistics available

Signal	Metric	Observed	Rule	Severity
battery_temp_c	maximum	45.5	> 45.0	critical
soc_pct	maximum	91.2	> 88.0	info
brake_pressure	maximum	86.0	> 82.0	warning
can_id_18ff50e5	period drift	12.7 ms	> 10.0 ms	warning

AI and reports

AI assists the report, but engineering evidence stays in control.

AI narrative drafts are generated from stored project metadata, processed signal statistics, and findings. Request logs preserve provider, model, prompt version, context hash, token counts, and review outcomes.

Project metadata

Processed signal statistics

Rule findings

Prompt context hash

AI draft

Human approval

Report attachment

Explore the live engineering workspace

The dev environment already contains sample projects, log files, rules, findings, reports, and the format registry foundation for the next parser plugins.

Open app