OctoAI vs Scribble Data

Neither company has publicly disclosed a valuation, making a definitive size comparison difficult. OctoAI employs 100-500 people, while Scribble Data has 10-50 employees.

OctoAI has raised $132M in disclosed funding across 0 known rounds. Scribble Data's funding history is not publicly available.

OctoAI holds the higher Awaira Score at 65/100, compared to Scribble Data's 35/100. The Awaira Score is a composite metric factoring in valuation, funding, stage, team size, and market presence — a 30-point gap that reflects meaningful differences in scale or traction.

OctoAI was founded by Luis Ceze in 2019. Scribble Data was founded by Arun Iyengar in 2019. Visit each company's profile on Awaira for a full founder biography.

OctoAI: OctoAI delivers a machine learning acceleration and model serving platform that enables teams to deploy, scale, and optimize AI models in production with significantly lower inference latency and cost compared to standard cloud ML services. The platform includes automated model optimization, hardware-aware compilation, and a managed serving layer that handles traffic routing and autoscaling.\n\nThe company raised approximately 132 million USD and counts enterprise customers in sectors including e-commerce, media, and financial services that operate high-throughput model serving pipelines at scale. OctoAI emerged from foundational research at the University of Washington in ML systems optimization, giving the technical team a deep background in compiler-level model performance.\n\nAs inference costs become the dominant expense in production AI deployments, infrastructure that reduces cost-per-query by meaningful percentages translates directly to enterprise budget savings. OctoAI competes with Anyscale, BentoML, and cloud-native MLOps offerings, but its focus on hardware-level optimization and the depth of its model acceleration capability distinguishes it from platforms that primarily address deployment workflow rather than raw performance. Scribble Data: Scribble Data builds a feature store and ML data pipeline platform that enables data science teams to define, compute, store, and serve machine learning features in a unified platform, addressing the significant engineering overhead of building and maintaining feature infrastructure for production ML systems. The platform reduces the time data teams spend on data wrangling and feature engineering by providing reusable feature definitions and automated pipeline orchestration.\n\nThe company is in early Seed stage with limited disclosed funding and targets data science teams at financial services companies, digital consumer businesses, and enterprise analytics organizations that run large-scale ML operations. Scribble Data positions its platform as infrastructure that shortens the path from model ideation to production deployment.\n\nFeature stores have emerged as a recognized production ML infrastructure category, with vendors including Tecton, Feast, and Hopsworks competing for enterprise adoption. Scribble Data's India-based team and pricing model target a segment of the market that cannot justify the cost of US-headquartered enterprise ML platform vendors, while still requiring production-grade feature management capabilities.

Both OctoAI and Scribble Data were founded in the same year — 2019. Despite sharing a founding year, they may have launched at different times within that year, which can matter in fast-moving AI markets.

OctoAI has approximately 100-500 employees, while Scribble Data has approximately 10-50. A larger team often signals higher revenue or venture backing, but in AI, smaller teams are increasingly capable of building at scale.

Yes, OctoAI and Scribble Data are direct competitors — both operate in the ML Platform space and likely target overlapping customer segments. This comparison is especially relevant for buyers evaluating both platforms.