Shakudo

Research Team Data Published Compare

Summary

Data and AI operating system that orchestrates best-of-breed AI, ML, data, and agent infrastructure inside enterprise VPC/on-prem environments.

Description

Shakudo provides an AI operating system deployed in customers’ own infrastructure with an AI Gateway, stack orchestration, model/data integrations, security controls, RBAC, and sovereign AI deployment patterns.

Positioning

Operating System for AI / sovereign enterprise AI infrastructure

Key facts

HQ location
San Francisco, CA, USA and Toronto, Canada
Founded
2021
Employee range
11-50 (~35 (BetaKit Feb 2026; LinkedIn range 11-50))
Funding stage
Series A
Company type
Private
Pricing model
Custom Quote Subscription (Enterprise SaaS / demo-based pricing; deployed in customer VPC / cloud / on-prem)
Last updated

Financials

Revenue estimate
Undisclosed (Latka estimates $4.8M ARR for 2024; BetaKit says 2026 annual sales now exceed last raise amount)
Valuation estimate
Undisclosed (BetaKit reported a significant bump vs. Series A, but no valuation)
Investments
~$18M total raised (incl. $7.2M Series A led by GreatPoint Ventures in 2023; $7M strategic round in 2026)

Relationships

Target customers
Regulated enterprises and data/AI teams in financial services, healthcare, retail, manufacturing, real estate, energy, and government
Key competitors
Databricks, Snowflake, Dataiku, Domino Data Lab, DataRobot, AWS SageMaker, Google Vertex AI, Palantir AIP, Salt AI
Known customers
QuadReal, Loblaw Digital, CentralReach, Huntington Bank, BWX Technologies, Gallo, Whitecap Resources

Classification (raw research text)

Core focus
Enterprise AI orchestration, AI gateway, data/AI stack automation, and sovereign AI deployment
Core industry
Enterprise AI infrastructure
Core category
Data and AI operating system / AI orchestration platform

Shown verbatim from the research spreadsheet — deriving structured industry tags from this text is a future phase.

Segments, Industries & Certifications

Segments

AI Workflows, AI Agents, LLM Fine-tuning, AI Developer Tools, Knowledge & RAG, LLM Deployment, AI Quality & Observability, Traditional ML, AI Governance & Risk, Chatbots, Analytics & BI