Reasoning over extremely large amounts of data under uncertainty is one of the most fascinating problems in computer science.
In this first of many under-the-hood posts, we describe how we think about incident investigation at @DeductiveAI as an online hypothesis-ranking problem, applying incremental Bayesian inference to maintain and update a posterior over competing root-cause hypotheses as noisy (and sometimes, even contradictory) observations arrive at scale.
If you care about probabilistic reasoning, causal inference, and building agents that operate under real-world uncertainty, you’d really enjoy this one: https://t.co/WGs3zVs97y
.@DeductiveAI raised $7.5 million in Seed funding led by @CRV, a StepStone platform manager, as it launches its AI SRE agents that diagnose and remediate software failures in minutes. Full breakdown here: https://t.co/4HpQAHS7EK
Deductive AI (@DeductiveAI) raises a $7.5M Seed (@CRV, @databricks Ventures, @thomvest), enabling founders Rakesh Kothari and @sagrw to build an AI reasoning engine that diagnoses distributed system failures in seconds. Their cognitive RCA platform is slashing incident resolution times and giving engineering teams back thousands of productive hours.
Let’s keep the conversation going on LinkedIn: (https://t.co/6Ay9rwHd2P)
Full rundowns live 👉 https://t.co/3putaTjOb6
Work with me here 👉 https://t.co/RgpoflQU3x
#Startups #StartupFunding #EarlyStage #VentureCapital #SeedRound #AI #AIAgents #Automation #RootCause #RCA #Data #DataDriven #Infrastructure #Enterprise #EnterpriseTech #EnterpriseAI #SaaS #Technology #Innovation #TechEcosystem #StartupEcosystem #Hiring #TechHiring
Over the past year, we’ve been focused on a simple idea: engineers shouldn’t have to sift through dashboards, logs, and code to understand why something broke.
Working with several amazing customers like @DoorDash, @Foursquare , and @Kumo_ai_team, we’ve seen the same pattern across fast-moving teams. Complex systems, scattered signals, and engineers piecing together the story of an incident from scratch every time.
We built @DeductiveAI to change that. By bringing code, metrics, and logs into a single reasoning surface, it gives engineers a clear, end-to-end understanding of what happened and why, so they can get back to building.