About
Deeptrace builds AI SRE agents for engineering teams that investigate and resolve production alerts end-to-end. Its product reasons across observability, telemetry, logs, metrics, traces, and code to surface evidence-backed root causes, reduce alert fatigue and mean time to resolution, and help fast-growing startups through F1000 enterprises operate reliably without adding on-call headcount.
Market
Deeptrace competes in AI-native SRE, production incident response, and observability automation for engineering organizations seeking to reduce alert fatigue and mean time to resolution. It differentiates by investigating alerts end-to-end across telemetry and code, maintaining a living knowledge graph of the customer’s architecture, and moving from diagnosis to automated remediation through pull requests, documentation updates, and tickets rather than stopping at alerting or incident coordination.
Deeptrace targets fast-growing startups through F1000 enterprises with complex production systems and engineering teams that cannot afford downtime. Its primary buyers and users are CTOs, VPs/directors of engineering, SRE teams, and software engineers responsible for on-call reliability, alert triage, and incident resolution.
At a Glance
Problem
Modern engineering teams spend substantial time maintaining and debugging production systems, while triaging, finding the root cause of, and resolving alerts slows engineering velocity. The central pain is alert fatigue and context switching: engineers must piece together evidence across multiple systems while customers are still exposed to outages or degraded service. The killer use case is automatically investigating production alerts quickly enough to prevent them from becoming customer-visible incidents, allowing a lean team to operate a growing system without proportionally increasing on-call headcount.
Product / Service
Deeptrace is an AI SRE platform that investigates and resolves production alerts end to end. It reasons across logs, traces, metrics, observability data, telemetry, and application code; ranks and groups alerts, attaches evidence-backed root-cause context, and delivers findings through Slack or its web application. The company says its investigations reach a root cause in an average of two to three minutes, and its agents can move from diagnosis to action by generating pull requests, updating runbooks or documentation, and creating Linear tickets.
The delivery model is trial- and demo-led, with startup plans offering a two-week trial and enterprise plans offering a four-week trial, tailored investigation capacity, and SaaS, hybrid, or self-hosted deployment. The intended benefit is lower mean time to resolution, less firefighting, and greater reliability without adding equivalent SRE or on-call staffing.
Market
Deeptrace competes in the emerging AI SRE, AI-powered incident response, production debugging, and observability-automation market. Its positioning overlaps with established alerting, observability, and IT service-management platforms, although the evidence reviewed does not establish a definitive direct-competitor list; one directory result names ServiceNow Knowledge Center as a possible alternative. Deeptrace differentiates itself by promising autonomous investigation across telemetry and code, rather than only alert routing, dashboards, or runbook access.
The company is an early commercial-stage startup founded in 2025 and backed by Y Combinator’s Fall 2025 batch. Its YC profile says it is already seeing reduced time spent triaging, investigating, and resolving alerts in production with fast-growing companies, while its website identifies users or advocates at companies including Opendoor, Parafin, Traba, and Rain and says it is trusted by startups through F1000 enterprises. The site also announces a $5 million seed round. Public materials disclose trials, customer testimonials, and production usage, but do not disclose revenue or ARR, so paid scale and whether the business is meaningfully revenue-generating cannot be determined.
Founders & Leadership
Funding History
Felicis, Matrix
Recent News
StartupIntros reports that Deeptrace has raised $5.0 million across one funding round, most recently a $5 million seed round in March 2026.
Deeptrace published a case study describing its partnership with Mintlify, where Deeptrace investigates roughly 100 daily alerts using Datadog, GitHub, and Slack integrations. Mintlify reports reducing investigation time from about five minutes to one minute per alert and saving approximately eight hours of on-call work each day.
Deeptrace announced a $5 million seed round co-led by Felicis and Matrix, with participation from Y Combinator. The company said teams including Opendoor, Mintlify, and Phantom were using Deeptrace to investigate production alerts automatically.
Deeptrace published an engineering article arguing that keyword-based log analysis fails at scale and explaining how semantic understanding can improve production debugging.
Deeptrace published a culture article about rethinking incident response and on-call practices to protect engineering teams from burnout.
Shyft profiled Deeptrace as an AI-powered on-call support tool that automates incident detection, real-time alerts, and incident-management tasks.
Crunchbase described Deeptrace as developing AI SRE agents that detect, investigate, and resolve production incidents, and listed Felicis and Matrix among the seed investors.
Y Combinator introduced Deeptrace as an AI SRE that investigates and resolves production alerts end-to-end. Its launch description says the product can investigate issues from alert to pull request using logs, traces, metrics, and codebase context.
Active Roles
1Business Model
Deeptrace appears to monetize as a B2B software service through startup and enterprise offerings. Its public pricing page describes startup and enterprise trials, with enterprise plans featuring capacity tailored to alert volume, flexible deployment, dedicated support and SLAs, and custom integrations; exact prices are not publicly listed.