Overview
Run:ai (acquired by NVIDIA) develops AI workload orchestration and GPU cluster management software for AI training and inference. Enables efficient GPU resource allocation for autonomous driving, robotics, and large-scale AI model training. Based in Tel Aviv.
Verified record
- Verified deployments
- None on file
- Active incidents
- None on file
Valuation of record
DEPLOY VERIFIEDAcquisitionAcquired by NVIDIA
Key facts
HQ
Founded
Parent
Product
Data & sources
Web sources
1
1 source backing this record.View all →
Run:ai on the deployment map
View the global mapRun:ai has no verified deployments on the DEPLOY registry yet. Explore the deployment map by place and type.
No verified deployments for Run:ai on the DEPLOY record yet. Track Run:ai to know the moment the first one is verified.
Safety record
No incidents on record for Run:ai.
Only active incidents are counted. Retracted incidents are excluded from this summary but remain reachable at their canonical URLs.
Full safety record: incidents, sourcing, and exposure data →
Recent coverage
Run:ai in third-party press
Financial state
- Reporting basis
- aggregator_estimate
- Lifecycle stage
- acquired
- Counterparty risk class
- moderate
Each numeric field carries its own basis marker. Aggregators report a number; this surface preserves the source class so verification depth travels with the value.
Acquisitions (1)
- acquired by NVIDIAfull acquisition2024-04-24
Recent activity
Every change to this record is dated, sourced, and independently verified where marked.
- Record createdJun 25, 2026
Added to the verified registry
Sources (1)
Common questions
What is Run:ai?
What does Run:ai make?
Is Run:ai publicly traded?
How can I invest in Run:ai?
Where is Run:ai headquartered?
Who owns Run:ai?
Is Run:ai a top robotics company?
When was Run:ai founded?
Is Run:ai safe?
Methodology: Verified · 1 source (no primary) · last reviewed 2026-08-05
Verification posture
Verified
Low confidence
Review state
Stable
Last reviewed 2026-08-05
Sources by quality tier
- 1
- unclassified
- Unclassified source
The framework is documented at /methodology. Corrections at /corrections. Reviewer: DEPLOY editorial team.
Methodology surface for Run:ai.In the press
Recent coverage mentioning Run:ai from third-party publications. Automatically surfaced; not part of the verified registry record.
Meta’s New Open-Weight Model Can Run AI Agents on Your Laptop
Meta Glimmer is a bit smaller than the company’s closed-weight Muse Spark models.
Behind AI-for-Science Frenzy, Infrastructure Becomes the Decisive Variable
AI-generated hypotheses outrun AI-verified experiments. MegaRobo's ten-year bet is rebuilding lab tools for machines, not humans, and shipping closed-loop…
Popular open source AI developer tool Ollama raises $65M, grows to nearly 9M users
Benchmark-backed Ollama has amassed 176,000 stars, and nearly 17,000 forks on GitHub by helping developers easily run AI on their PCs.
Intel told me not to wear deodorant to visit its AI chip factory. Then I saw why. - Business Insider
<a…
I visited Intel's robot-run AI chip factory, where the biggest danger is human skin and hair - AOL.com
<a…
Nvidia Enters the PC Market with RTX Spark to Run AI Agents Locally - MIT Sloan Management Review Middle East
<a…
LG Electronics Quadruples As Nvidia AI Meeting Fuels Robotics Rally - TradingView
<a…
Nvidia Unveils AI PC Chip as Industry Bets on Autonomous AI Agents - Electronics For You BUSINESS
<a…
Intel stakes new claim in physical AI with robotics chips - Computerworld
<a…
Automation Anywhere: EnterpriseClaw Launches To Run AI Agents Across Enterprise Systems With Cisco, NVIDIA, Okta, And OpenAI - Pulse 2.0
<a…
Running AI Coding Agents for 13 Days Straight: A Practical Guide - SitePoint
<a…
Bluehost Introduces GatorClaw: The Simplest Way to Build and Run AI Agents for Small Business - PR Newswire
<a…
Machine-readable surfaces
- Markdown mirror: /companies/run-ai.md
- RSS feed: /companies/run-ai/feed.xml
- JSON-LD: embedded in this page’s head
- REST API: /v1/companies/10756208-aa33-4e79-8a7c-17c84662ce72
- Revision history: /companies/run-ai/history
- Data documentation: /data
- Query this programmatically: Deploy MCP
Reality vs attention
Not enough verified signal yet to place Run:ai against peers. Reality and attention percentiles publish once the underlying record clears its data floor.
6-month trend
Analysis
Limited public funding data for capital position assessment.
Signal flags
Dimension breakdown
Verified signal
Attention (reach, not merit)
DEPLOY Intelligence scores are computed from verified registry data: confirmed deployments, disclosed funding rounds, regulatory filings, active job listings, video viewership, and press coverage. Confidence ratings reflect data availability. Scores update nightly.
DEPLOY Indices — verified vs claimed
Last computed: Aug 18, 2026