Tiresias is the AI layer that takes the photograph of your codebase, then watches it day-by-day. Code quality, AI footprint, architecture decisions — measured continuously inside your repo. When something breaks, your CTO knows before the customer does.
A code audit is true at the timestamp it was run — and obsolete the moment your team pushes. In an AI-augmented codebase, drift is no longer rare. It's the default state.
A point-in-time audit is true at the moment it's signed. Every merge after that invalidates the baseline. After one quarter the report is folklore — it doesn't inform a single architectural decision your team is actually making.
Copilot, Cursor, Claude write code that compiles but routinely violates the patterns your senior engineers care about. AI-slop ships to production because nobody is watching the volume of generated code — it grows quietly until a CVE finds it for you.
For startups and scale-ups under 30 developers, a full-time senior CTO is unaffordable. But architectural decisions — build vs buy, vendor lock-in, GenAI strategy — won't wait for the next Series A. Without one, technical debt compounds in silence.
Stop running point-in-time audits.
Start running a continuous signal.
Tiresias replaces the quarterly PDF with a live dashboard. Re-scan on every push. Threshold breach → alert in <60 seconds. Your CTO opens it every morning — not once a quarter.
A one-off photograph of the codebase to set the baseline, then a monthly subscription sized to your codebase. No flat fee, no surprise — pricing reflects how big and complex your repo actually is.
The photograph of the project at day zero. Output: AQI baseline, threat model, prioritized risk map, monitoring configuration. The cost is absorbed into CTO days — sized by a set of factors, not a flat fee.
Tier sizing is indicative — final scope confirmed after a free repo scan. Full pricing and SLA in the dedicated Tiresias deck.
A closed feedback loop. Each alert produces an Architecture Decision Record. The output of the SAL updates the thresholds. Nothing stays static.
Full scan of every Git repository you connect. The AQI (Architecture Quality Index) baseline is set, the threat model is generated, the monitoring configuration is calibrated. The codebase has its first photograph.
Every push triggers a re-scan. Static analysis + DORA metrics + AI footprint detection run continuously. The dashboard is always live — your CTO doesn't wait for a quarterly report to know what's happening in the repo.
Threshold breach — a security regression, a code-health drop, an AI-footprint spike — fires a Slack/webhook alert in under 60 seconds. Not "next month in the report". Now, while the deploy is still fresh.
For alerts that warrant judgment, a senior CTO — validated through Skillsdex — runs a SAL (Service Activity Log) on-demand. Output: an Architecture Decision Record, a remediation backlog, an updated threshold. The loop closes.
Since Q2 2026, EU regulators expect a continuous, auditable signal on AI code footprint and security posture — not a yearly PDF. Tiresias was built for this.
Your repository content never leaves the EU. Inference, storage and logs all on EU infra.
Type II audit in progress — operational controls aligned with what enterprise procurement asks for.
The continuous AI-footprint signal that regulators expect — already built into the platform.
We run Tiresias on a single repo you point us to. You walk away with a baseline AQI score, a risk map and an honest read on whether you need continuous monitoring — without committing to anything.