Squid
Product & Competitive Intelligence
AI-powered collaborative platform for electric grid planning and scenario simulation for utilities.
Company Overview
Builds an AI-powered, collaborative SaaS platform for electric grid planning and modeling that uses machine learning to automate scenario simulation, predictive analytics, and evidence-backed decision-making for utilities and grid operators.
Competitive Advantage & Moat
Product Roadmap & Public Announcements
Squid has publicly announced a unified, versioned grid model workspace with evidence and assumption attachment, repeatable AI-driven workflows for planning, connections, and network change, and browser-based collaborative grid modeling. They highlight SOC 2 Type II and ISO 27001 certifications, named enterprise customers (National Grid, Octopus Energy), and a testimonial from Octopus Energy's Head of Flexibility Markets describing active production use. Their public thesis centers on one trusted network model replacing fragmented file-based workflows as electrification accelerates.
Signals & Private Analysis
Given both founders' backgrounds at Octopus Energy and AWS, there are strong indicators of a cloud-native, API-first architecture designed for enterprise-scale deployment. GitHub and hiring patterns suggest investment in ML infrastructure, data engineering, and energy-domain expertise. Conference and industry appearances hint at partnerships with DNOs (Distribution Network Operators) and DSOs (Distribution System Operators) in the UK and Europe. There are also signals of a roadmap toward DER (Distributed Energy Resource) integration, real-time grid optimization, and compliance/audit tooling for regulated utility environments.
Product Roadmap Priorities
AI agents automate the creation, updating, and stress-testing of grid models, enabling planners to simulate network changes, new connections, and infrastructure upgrades in real time.
Instead of manually updating spreadsheets and running slow simulations, Squid's AI builds a live digital twin of the grid and lets planners instantly test "what if" scenarios, like adding a new solar farm or upgrading a substation, without breaking a sweat.
It's like having a SimCity AI that not only builds your city but also tells you exactly which roads will flood if you add a new power plant—before you make the mistake.
ML models forecast demand, asset health, and DER (Distributed Energy Resource) impacts to inform long-term infrastructure investment and maintenance decisions.
The AI looks at years of data about how much electricity people use, how old the equipment is, and where new solar panels are popping up—then predicts what the grid will need next year, or in ten years, so utilities can plan ahead.
It's like a weather forecast for the grid—except instead of rain, it predicts where the lights might go out and what needs fixing before it happens.
AI automates the ingestion, linking, and versioning of grid, market, and flexibility data, attaching evidence to every planning decision for auditability and transparency.
The AI automatically pulls in data from dozens of sources, organizes it, and stamps every planning decision with a receipt showing exactly what information was used, so when regulators ask "why did you do that?", the answer is already there.
It's like Google Docs for the grid—every edit is tracked, every decision has a footnote, and you can always see who changed what and why.
Company Overview
Key Team Members
- Conor Jones, Co-founder,
- George Kolokotronis - Co-founder
Founder Force Multiplier
Squid combines deep operational experience from National Grid and Octopus Energy, two of the UK's most innovative grid and retail energy companies, with world-class cloud engineering expertise from AWS. This allows them to build AI-powered tools that understand both the technical realities of grid infrastructure and the workflow pain points of utility planners, bridging the gap between legacy systems and modern, scalable software.
Funding History
- 2025 | Conor Jones and George Kolokotronis co-found Squid.
- 2026 | Accepted into Y Combinator Winter 2026 batch
Competitors
- Traditional Grid Planning Tools: PSS, ETAP, DIgSILENT PowerFactory, GE PSLF.
- Legacy Utility Software: Oracle Utilities, SAP for Utilities, OSIsoft
- AI-Native Energy/Grid Startups: Utilidata, Sense, Amperon, GridBeyond
