
11 - 50 employees
🤖 Artificial Intelligence
☁️ SaaS
🤝 B2B
🔥 Funding within the last year
💰 Seed on 2025-07
Artificial Intelligence • SaaS • B2B
Traversal is an AI-driven Site Reliability Engineering (SRE) platform that automates incident detection, triage, root cause analysis, and remediation for complex production environments. It uses agentic AI to cut through alert noise, surface evidence-backed root causes, and enable one-click rollbacks or fixes, while generating editable post-mortems and supporting flexible deployment models (read-only, on-prem, bring-your-own-model) to meet enterprise privacy and control requirements.
🔥 0 minutes ago
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11 - 50 employees
🤖 Artificial Intelligence
☁️ SaaS
🤝 B2B
🔥 Funding within the last year
💰 Seed on 2025-07
Artificial Intelligence • SaaS • B2B
Traversal is an AI-driven Site Reliability Engineering (SRE) platform that automates incident detection, triage, root cause analysis, and remediation for complex production environments. It uses agentic AI to cut through alert noise, surface evidence-backed root causes, and enable one-click rollbacks or fixes, while generating editable post-mortems and supporting flexible deployment models (read-only, on-prem, bring-your-own-model) to meet enterprise privacy and control requirements.
• Own all four adoption phases end-to-end for a portfolio of enterprise accounts, from first post-deployment kickoff through renewal signature. • Maintain a customer-specific 30/60/90 roadmap, updated weekly and reviewed in every customer sync. • Run every customer-facing meeting type in the process: kickoffs, team enablement sessions, bi-weekly product feedback calls, power-user 1:1s, weekly syncs, exec/leadership syncs, and Quarterly Business Reviews. • Publish a monthly async leadership update to each account’s executive sponsors — written, concise, and built on real usage data. • Own customer-specific integrations, custom prompt engineering, and edge-case debugging for each assigned account. • Instrument and maintain accuracy tracking in collaboration with the customer — ensuring the dataset is customer-owned and credible, not vendor self-reported. • Identify and capture failure modes through power-user 1:1s, then work with the product team to translate them into roadmap items. • Debug and resolve platform issues surfaced during adoption, coordinating with engineering when needed.
• 5+ years in a technical customer-facing role: solutions engineering, solutions architecture, technical account management, or customer success engineering at an enterprise software or infrastructure company. • Genuine technical depth — you can read logs, understand distributed systems failures, and have a point of view on why an AI agent produced a wrong root cause. • Demonstrated ability to run executive-level conversations and engineer-level conversations in the same week with the same customer. • Experience driving adoption of a technical product with a complex, multi-stakeholder customer. • Strong written communication. • Comfort with ambiguity and a builder's instinct.
• competitive compensation • startup equity • health insurance • flexible time off • plenty of in-office snacks
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