DevRev vs Celonis

By valuation, Celonis is the larger company at $13B versus $1.2B — a 11.3x difference. Size can also be measured by team: DevRev employs 200-500 people while Celonis has 1000+ employees.

Celonis has raised more in total funding at $2B, compared to DevRev's $158M — a gap of $1.8B. Combined, the two companies have completed 4 known funding rounds.

Celonis leads with an Awaira Score of 90/100, while DevRev sits at 63/100. That 27-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

DevRev was founded by Dhruv Jain in 2020. Celonis was founded by Alexander Rinke in 2011. Visit each company's profile on Awaira for a full founder biography.

DevRev: DevRev is an AI-powered platform that connects product development and customer success workflows, enabling companies to link customer issues, feature requests, and support tickets directly to engineering work items, creating a continuous feedback loop between what customers experience and what developers build. The platform combines CRM, issue tracking, and AI-powered customer insight synthesis into a unified product-led growth tool.\n\nThe company raised approximately $100M from investors including Khosla Ventures and Mayfield Fund, with a founding team that includes veterans from Nutanix with a track record of building enterprise infrastructure companies. DevRev has attracted customers among SaaS companies seeking tighter alignment between go-to-market and product development organizations.\n\nThe traditional separation of CRM and engineering tools creates significant information loss as customer feedback fails to systematically inform product prioritization. DevRev's integrated approach addresses this alignment problem with AI that surfaces customer-validated priorities for engineering teams, targeting a workflow integration gap that has been underserved by both CRM vendors and project management tools. Celonis: Celonis builds a process mining and execution management platform that uses machine learning to extract, visualise, and optimise business processes from event log data in enterprise systems including SAP, Oracle, Salesforce, and ServiceNow. The Munich company platform connects to enterprise software transaction records, reconstructs actual business process flows from data, identifies inefficiencies and compliance deviations, and provides AI-powered recommendations for process improvement.\n\nThe company raised approximately $1.4 billion including a $1 billion Series D round in 2021 from investors including Arena Holdings, Durable Capital, and T. Rowe Price, valuing it at $13 billion and making it one of Germany most valuable private technology companies. Celonis counts over 1,000 enterprise clients including Siemens, Uber, 3M, and Vodafone, with large deployments across order-to-cash, procure-to-pay, and accounts payable processes generating measurable working capital improvements and operational cost reductions.\n\nCelonis created the process mining software category and competes against SAP Signavio, IBM Process Mining, and Minit in a market it largely invented. The company has expanded from analytical process mining tools into execution management, embedding AI recommendations directly into enterprise workflows rather than producing reports for human review. This execution layer differentiates Celonis from pure analytics vendors and creates a stickier product that becomes embedded in operational processes rather than consumed as a standalone analysis tool.

Celonis got there first, launching in 2011 — that's 9 years of extra runway. DevRev didn't arrive until 2020. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

DevRev has about 200-500 employees; Celonis has about 1000+. A bigger team usually means more revenue or heavier VC backing, but in AI, small teams can build at massive scale.

Yes — they're direct rivals. Both DevRev and Celonis compete in Enterprise AI, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.