Overall Winner: Improbable·68/ 100

Improbable vs Scribble Data

In-depth comparison — valuation, funding, investors, founders & more

Winner
I
Improbable

🇬🇧 United Kingdom · Herman Narula

Series CML PlatformEst. 2012

Valuation

N/A

Total Funding

$700M

68
Awaira Score68/100

500-1000 employees

Full Improbable Profile →
S
Scribble Data

🇮🇳 India · Arun Iyengar

SeedML PlatformEst. 2019

Valuation

N/A

Total Funding

N/A

35
Awaira Score35/100

10-50 employees

Full Scribble Data Profile →
🔬

Analyst Summary

Generated from real data · No AI hallucinations

Both Improbable and Scribble Data compete directly in the ML Platform space, making this a head-to-head matchup within the same market segment. Improbable develops large-scale simulation technology and virtual world infrastructure, originally focused on cloud-distributed game server simulation and subsequently pivoting to AI-powered synthetic environment generation and metaverse platform development. 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.

Neither company has publicly disclosed a valuation at this time. Improbable has raised $700M in disclosed funding.

Improbable has 7 years more market experience, having been founded in 2012 compared to Scribble Data's 2019 founding. In terms of growth stage, Improbable is at Series C while Scribble Data is at Seed — a meaningful difference for investors evaluating risk and upside.

Improbable operates out of 🇬🇧 United Kingdom while Scribble Data is based in 🇮🇳 India, giving each a distinct home-market advantage. On Awaira's 0–100 composite score, Improbable leads with a score of 68, reflecting stronger overall fundamentals across valuation, funding, and growth signals.

Metrics Comparison

MetricImprobableScribble Data
💰Valuation
N/A
N/A
📈Total Funding
$700M
N/A
📅Founded
2012
2019WINS
🚀Stage
Series C
Seed
👥Employees
500-1000
10-50
🌍Country
United Kingdom
India
🏷️Category
ML Platform
ML Platform
Awaira Score
68WINS
35

Key Differences

📅

Market experience: Improbable has 7 years more (founded 2012 vs 2019)

🚀

Growth stage: Improbable is at Series C vs Scribble Data at Seed

👥

Team size: Improbable has 500-1000 employees vs Scribble Data's 10-50

🌍

Market base: 🇬🇧 Improbable (United Kingdom) vs 🇮🇳 Scribble Data (India)

⚔️

Direct competitors: Both operate in the ML Platform market segment

Awaira Score: Improbable scores 68/100 vs Scribble Data's 35/100

Which Should You Choose?

Use these signals to make the right call

I

Choose Improbable if…

Top Pick
  • Higher Awaira Score — 68/100 vs 35/100
  • Stronger investor backing — raised $700M
  • More market experience — founded in 2012
  • United Kingdom-based for regional compliance or proximity
  • Improbable develops large-scale simulation technology and virtual world infrastructure, originally focused on cloud-distributed game server simulation and subsequently pivoting to AI-powered synthetic environment generation and metaverse platform development
S

Choose Scribble Data if…

  • India-based for regional compliance or proximity
  • 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

Users Also Compare

FAQ — Improbable vs Scribble Data

Is Improbable bigger than Scribble Data?
Neither company has publicly disclosed a valuation, making a definitive size comparison difficult. Improbable employs 500-1000 people, while Scribble Data has 10-50 employees.
Which company raised more funding — Improbable or Scribble Data?
Improbable has raised $700M in disclosed funding across 0 known rounds. Scribble Data's funding history is not publicly available.
Which company has a higher Awaira Score?
Improbable holds the higher Awaira Score at 68/100, 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 33-point gap that reflects meaningful differences in scale or traction.
Who founded Improbable vs Scribble Data?
Improbable was founded by Herman Narula in 2012. Scribble Data was founded by Arun Iyengar in 2019. Visit each company's profile on Awaira for a full founder biography.
What does Improbable do vs Scribble Data?
Improbable: Improbable develops large-scale simulation technology and virtual world infrastructure, originally focused on cloud-distributed game server simulation and subsequently pivoting to AI-powered synthetic environment generation and metaverse platform development. The London company built SpatialOS, a cloud platform for running distributed simulations of large, persistent virtual worlds, and has applied simulation capabilities to defence, urban planning, and entertainment applications.\n\nThe company raised approximately $700 million including a landmark $502 million SoftBank round in 2017 that was one of the largest venture rounds in European technology history. Improbable has undergone multiple strategic pivots, moving from gaming infrastructure to defence simulation contracts with clients including the UK Ministry of Defence, which uses simulation environments for training and wargaming. The company also built MSquared, a metaverse interoperability network, before refocusing on defence and AI simulation work.\n\nImprobable operates in an AI simulation market where demand from defence agencies, autonomous vehicle companies, and robotics firms has grown substantially. The company competes with simulation platforms from Epic Games (Unreal Engine), NVIDIA (Omniverse), and specialist defence simulation vendors. Its SoftBank backing and large cash reserves have enabled it to survive multiple market pivot cycles that would have ended less well-funded companies, and its current focus on AI-powered synthetic data generation for defence represents a growing government budget category. 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.
Which company was founded first?
Improbable was founded first in 2012, giving it 7 years of additional market experience. Scribble Data was founded later in 2019. In AI, even a year or two of head start can translate into significantly more training data, customer relationships, and institutional knowledge.
Which company has more employees?
Improbable has approximately 500-1000 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.
Are Improbable and Scribble Data competitors?
Yes, Improbable 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.