Oodle

IMPORTANT DATA-QUALITY NOTE: This research brief described the target as an 'industrial AI/manufacturing analytics company' and a 'Greylock Partners portfolio company.' Exhaustive checks of Oodle's own website (homepage, /company, /product, /customers, footer, and JSON-LD structured data), its Crunchbase organization record, its blog (blog.oodle.ai, 25 posts reviewed), and Greylock's own public portfolio page found zero evidence supporting either premise. The company that actually operates at the domain oodle.ai is an AI-native, developer-focused observability/APM platform -- not an industrial or manufacturing analytics company -- and its disclosed investors are Pear VC, Engineering Capital, and SNR VC (plus individual angels), not Greylock. This profile documents the real, verifiable oodle.ai company as found; the Greylock relationship and industrial-AI categorization from the brief should be treated as unconfirmed/likely mismatched rather than as established fact. Oodle AI was founded in 2023 by Kiran Gollu (CEO) and Vijay Karthik (CTO), both veterans of Rubrik's cloud/data-platform engineering organization. Per the company's own bios, Gollu was Head of Cloud Platform Engineering at Rubrik (where he says he helped scale the business from roughly $5M to $600M in ARR), was previously co-founder/CEO of Neptune.io (a Y Combinator-backed observability startup), and was an early engineer on AWS S3 and DynamoDB. Karthik was a distributed-databases expert at Rubrik, where he architected a petabyte-scale file/object storage system supporting 5,000+ enterprise customers, was previously a tech lead on bidding and relevance ML systems at InMobi, and is an IIT Madras gold medalist. The founding thesis -- explicit in the company's marketing -- is that the team that helped build hyperscale storage and data-platform infrastructure at AWS, Rubrik, and Snowflake could re-architect observability (logs, metrics, traces, APM) around cheap, serverless, S3-native object storage instead of the expensive proprietary storage/indexing stacks used by Datadog, Splunk, and Elastic, delivering large cost reductions (Oodle advertises being roughly 3-5x cheaper than Datadog and, in earlier marketing, '10x the data at a 10th of the cost'). Oodle publicly launched its architecture in a December 18, 2024 blog post ('Oodle AI: Serverless, Cost-Efficient Observability'), initially positioning around PromQL-compatible metrics (Prometheus/Grafana replacement) and log search (Elastic/OpenSearch/Splunk/CloudWatch replacement). Reference customers that have since published case studies or on-site testimonials include Lookout (cybersecurity; VP Engineering Nagendra Swamy describes migrating 'thousands of nodes, dashboards, and alerts' off an eight-year Datadog deployment in six weeks), CureFit/Cult.fit (Platform Engineering Lead Kunal Khandelwal reports a 3x cost reduction after replacing Grafana), Zaggle (Indian fintech; CTO Srikanth Gaddam describes replacing CloudWatch, OpenSearch, and Splunk across ~200 services with a single faster search bar), Fello (Principal Engineer Ashish Gupta reports replacing Langfuse), WisdomAI, Bedrock Data, Labra, and smaller testimonial-only logos Fuel and Olyv. In a November 4, 2025 blog post ('Meet Oodle: Unified and AI-Native Observability'), the company repositioned around 'AI-native' debugging -- using LLM/agent-based natural-language query and root-cause-analysis workflows layered on top of its unified logs/metrics/traces/APM data -- coinciding with the broader 2025 AI-agent boom. By mid-2026 this had matured into a dedicated 'Agent Observability' product line (announced live via an on-site banner and supporting blog posts in July 2026, e.g. 'How we achieved $10/million agent spans' and 'You Can't Sample Your Way to Reliable Agents'), which adds LLM token tracking, cost estimation/attribution, prompt-and-response replay, and MCP (Model Context Protocol) integration for AI coding assistants like Cursor and Claude Code -- explicitly targeting Langfuse and other emerging LLM-observability tools as competitors alongside its original Datadog/Grafana/Elastic targets. Oodle appears to be an early-stage (seed), lean team: Crunchbase lists it at 11-50 employees and a Seed round led by Pear VC with an undisclosed amount and date; the company's own site lists Pear VC, Engineering Capital, and SNR VC as institutional backers alongside a group of operator-angels (the PagerDuty founder/YC general partner Andrew Miklas, Netskope co-founder/CEO Sanjay Beri, Shoreline founder Anurag Gupta, SNR VC's Kevin Mahaffey -- also founder of Lookout, which is separately an Oodle customer -- and Engineering Capital's Ashmeet Sidana). No independent press coverage (TechCrunch, Business Insider, trade press, etc.) of Oodle or its funding could be located via web search during this research; essentially all available detail comes from the company's own website, blog, and its Crunchbase listing, which itself flags founding/funding dates as 'obfuscated.' This sparse independent footprint, combined with the mismatch versus the research brief's premise, should be treated as a significant data-quality caveat for this profile.

Business model

B2B SaaS sold to engineering/DevOps/platform teams; usage-based and tiered pricing (including a free tier) with no per-host or per-seat fees; also sold via cloud marketplace commits (e.g., AWS Marketplace-style credits).

Usage/volume-based subscription pricing for logs, metrics, traces and APM ingestion/retention, plus a distinct usage-based price for AI-agent observability (advertised at $10 per million spans); free tier available.