AI Agent Conference 2026
The definitive gathering for autonomous and agentic AI systems. Founders, infrastructure engineers, enterprise leaders, and researchers shaping production-grade agents.
The Tribunal Engine deploys dozens of adversarial AI agents — anchored by a Prosecutor, Defender, and Judge — to debate root cause hypotheses with deterministic confidence scoring. Every verdict is defensible.
Deployed inside your VPC · Your data never leaves · Full audit trail
Pager fires. Bridge opens. Five engineers pile into a Slack thread. Two hours of scrollback, one hand-off to someone less qualified, a postmortem nobody trusts. Rooca delivers the verdict before the second pager fires.
03:28. Your pager fires. Don't wake your team.
Here is exactly how the Tribunal Engine works.
An incident alert fires from your monitoring stack, or an engineer manually triggers an investigation. The Evidence Collector Agent ingests the alert context and begins gathering evidence.
The Prosecutor gathers evidence from logs, metrics, traces, deployment histories, and code changes. It formulates a root cause hypothesis and assembles supporting evidence through structured analysis.
The Defender actively seeks counter-evidence, not as a formality but as adversarial challenge. It identifies contradictions, alternative explanations, and gaps in the argument.
The Judge evaluates both sides using deterministic scoring technology. It produces a composite confidence score that is reproducible: same evidence, same score. Every time.
The confidence-scored verdict is delivered with the complete reasoning trail: what the Prosecutor argued, what the Defender challenged, how the Judge adjudicated. Full audit trail. Defensible to auditors.
Rooca runs in your VPC. The verdict lands in Slack, routes through PagerDuty, and arrives as a DORA-ready audit document. Same evidence, same score, every time.
The verdict lands where your team already coordinates. Confidence score, cited sources, actionable summary. Zero dashboard context-switching.
Kubernetes NetworkPolicy deployed 22 min prior to incident restricted egress from checkout-svc to payments-db namespace. 94% of checkout requests blocked at connection establishment. Database itself operating nominally — downstream victim, not root cause.
A signed root cause document with full confidence decomposition and a reasoning trail auditors can replay. Same evidence, same verdict. Every time.
When the responder acknowledges, the investigation is already done. Rooca's verdict is attached to the incident before the human reads the first log line.
Mean time to resolution at a European energy infrastructure operator. First enterprise pilot.
Annual downtime loss per Global 2000 enterprise. Roughly 9% of operating profit.
Reduction in senior engineer investigation time per incident.
Pilot numbers are from a production deployment, not a demo environment. Industry numbers are sourced from public Global 2000 reporting.
The Tribunal Engine runs as AI agents inside your virtual private cloud. No SaaS relay, no external API calls carrying your telemetry, no model training on your data.
Every agent session produces an immutable audit trail: evidence gathered, hypotheses formed, challenges raised, and the deterministic confidence score computation.
Deterministic scoring ensures confidence outputs are reproducible. Same evidence, same score. Every time. Auditors and regulators can verify this independently.
Rooca does not bolt compliance onto a SaaS product. The architecture itself satisfies data residency, explainability, and audit trail mandates.
Each AI agent builds on the last. The Tribunal's strategies are self-evolving, with confidence thresholds determining how much autonomy each agent earns.
AI agents gather evidence, debate hypotheses, and deliver confidence-scored verdicts. The human engineer reviews and decides.
AI agents answer natural language questions about system state, grounded in real evidence from your infrastructure.
AI agents analyze patterns across historical incidents and telemetry baselines to identify failure conditions before they escalate.
AI agents propose infrastructure actions with confidence-scored justifications. The human approves before execution.
AI agents execute remediation autonomously when confidence exceeds threshold. Every action is logged, reversible, and bounded by policy.
When Rooca delivers a verdict, it is not a guess.
It is the stone of truth.
Rooca's plugin-based evidence collection architecture connects to your observability, cloud, incident management, communication, and code platforms.
Every Tribunal verdict includes a complete reasoning trail. EU AI Act transparency requirements are satisfied by the architecture.
Nowhere. Rooca deploys inside your VPC via Kubernetes Helm chart. No SaaS relay. No model trained on your data.
The Defender agent is structurally incentivized to find contradictions. Deterministic scoring ensures confidence reflects actual evidence strength.
Our first enterprise pilot reduced senior engineer investigation time by 95.5% per incident.
Rooca ships as a Kubernetes Helm chart. Initial deployment to first verdict typically takes days, not months.
Every verdict includes a confidence score and full deliberation record. Low-confidence verdicts are flagged for human review.
No. Rooca actively gathers evidence, forms hypotheses, challenges them with counter-evidence, and adjudicates through deterministic scoring.
The confidence score is the trust signal. High-confidence verdicts with resolved contradictions are reliable.
Datadog, Grafana, Prometheus, Zabbix, PagerDuty, Slack, GitHub supported out of the box. Custom plugins supported.
Single-pass inference is fast but fragile. Adversarial deliberation catches the false positives that cost your team hours.
Read article →The Digital Operational Resilience Act takes effect January 2025. Here is exactly what it means for your incident investigation workflow.
Read article →When AI replaces labor cost, not software cost, the pricing model must change.
Read article →Large language models are powerful but unpredictable. Rooca's patent-pending deterministic technology makes outputs auditable.
Read article →Rooca operates among the gatherings shaping autonomous AI, enterprise infrastructure, and the regulated software stack.
The definitive gathering for autonomous and agentic AI systems. Founders, infrastructure engineers, enterprise leaders, and researchers shaping production-grade agents.
One of the world’s leading technology conferences. Founders, investors, and operators exploring the future of AI infrastructure and enterprise software.
A citywide gathering of founders, builders, investors, and operators shaping Canadian technology and the next generation of AI innovation.
Rooca was born from a simple observation made across two decades of enterprise infrastructure: the most expensive moments in modern enterprise are not the outages themselves, but the hours of human reasoning required to understand why they happened.
Our co-founders bring more than twenty combined years across enterprise infrastructure, distributed systems, and applied AI, including prior startup leadership roles and successful founder exits. They have lived every phase of the reliability problem: 3 AM on-call rotations, post-incident review boards, and regulator briefings the morning after. They have watched senior reliability engineers, the most expensive technical talent in the enterprise, spend their nights chasing root causes that should have been found in minutes.
When generative AI matured, the obvious response was to point a single large model at the problem. That approach produced answers, but not defensible ones. Regulated enterprises cannot run mission-critical infrastructure on a system that gives one opinion and cannot show its reasoning. Auditors, CISOs, and compliance officers need to see how a conclusion was reached, why competing explanations were rejected, and what confidence the system has in its own verdict. The Tribunal Dialectic Engine was built to answer that demand: three specialized agents (a Prosecutor, a Defender, and a Judge) whose adversarial debate is arbitrated by a deterministic scoring layer no language model can override. The result is a verdict that is reproducible, auditable, and confidence-scored. The foundation for safe autonomy in regulated environments.
We built Rooca in Canada deliberately. The Canadian AI ecosystem, anchored by Creative Destruction Lab, Vector Institute, and MaRS Discovery District, with applied research communities spanning Toronto, Montreal, and Edmonton, is one of the world’s strongest concentrations of responsible AI thinking and reinforcement learning expertise. Canadian regulatory alignment with European frameworks (DORA, NIS2, EU AI Act, OSFI E-23) makes it the natural headquarters for an enterprise AI infrastructure company built around governance and auditability. Rooting Rooca here is a strategic decision, not a default one.
Today Rooca is in production with a European energy infrastructure design partner. Mean time to resolution has fallen from roughly four hours to eleven minutes. The category we are building, Autonomous Causal Intelligence, sits above monitoring, observability, and alerting. It is the layer where reactive debugging ends and deterministic autonomy begins.
We are hiring engineers who want to define a new category. Rooca is not another chatbot company. We are building the AI decision engine that regulated enterprises will trust.
See Open Positions →Rooca deploys inside your VPC. Your data stays yours. The demo uses synthetic infrastructure to show you exactly how the Tribunal investigates, debates, and delivers a confidence-scored verdict.