Ohm blog · May 2026
This post argues that engineering workflows need persistent data foundations, predictive intelligence in live pipelines, reusable workflows, and enterprise-grade governance rather than generic chatbots.
AI "co-scientists" for battery design & manufacturing
Company research
Public company, workplace, funding, and market signals
Overview
Ohm is a San Francisco-based enterprise AI platform, originally launched as Byterat, that helps hardware and battery engineering teams ingest test data, run predictive analytics, and delegate multi-step analyses to AI co-scientists.
Primary product
Agentic AI platform for hardware product development and test programs
Founded
2023
Headquarters
San Francisco, California, United States
Team size
1-10
Work style
Flexible
Industry
Software Development
Sub-industry
Enterprise AI platform for hardware engineering and battery data analytics
Offices
San Francisco, California, United States
Business model
enterprise SaaS
usage-based pricing
data-volume-based pricing
Funding
Stage
Seed
Total raised
$4.1M
Latest round
Seed · Oct 2023
Latest amount
$4M
People & investors
Leadership
Founder and CEO
Scientific Co-Founder / CSO
Head of Engineering
Work & culture
Lean, high-ownership early-stage team; self-described as engineers, ex-founders, sales leaders, and PhD battery scientists building in San Francisco; emphasis on speed, autonomy, and in-person collaboration.
Work style
Flexible
Visa sponsorship
Limited
Compensation
Public job postings show a Forward Deployed Engineer - Battery role at $120k-$160k base plus 0.25%-1.00% equity; other roles emphasize high ownership but do not disclose pay.
Benefits
Platinum health insurance
vision insurance
dental insurance
flexible PTO
team off-sites
Product & market
Pricing
Enterprise pricing; public historical signal indicates data-volume-based charging rather than per-user licensing.
Differentiators
- —AI co-scientists that execute multi-step engineering analyses in natural language
- —AI-ready data foundation that ingests and normalizes multi-modal test data
- —Predictive models embedded into live pipelines
- —Transparent generated code, hyperparameters, and methods
- —Reusable workflows and institutional knowledge that compound over time
- —Model-agnostic orchestration across vision, language, and time-series models
- —Native support for hardware-domain workflows such as battery test analysis and PyBaMM integration
Technology
TypeScript
Python
AWS
Go
LLM pipelines
time-series data
PyBaMM
natural language querying
agent infrastructure
Customers
Fortune 100 engineering teams
Fortune 10 technology companies
battery development teams
battery manufacturers
automotive OEMs
consumer electronics teams
aerospace teams
data center infrastructure teams
BMW
Competitors
Voltaiq
Micantis
Batalyse
Astrolabe
Accure
Qnovo
Eatron Technologies
Safion
Volytica Diagnostics
PowerUp
Scale & contact
Estimated revenue
≈$1.45M annual revenue estimate (public third-party estimate)
Estimated monthly visits
15.2K
Traffic estimate as of Jun 2026
Latest news
Ohm blog · May 2026
The company compares Ohm against legacy battery data platforms such as Voltaiq, Micantis, Batalyse, and Astrolabe, and lays out its broader automation, workflow, and knowledge-compounding claims.
Ohm blog · May 2026
Ohm’s launch post describes the platform as an enterprise AI system for engineering teams building physical products, with an AI-ready data foundation, predictive intelligence, and agentic co-scientists.
TechCrunch · Oct 2023
TechCrunch reported the company’s $4M seed round led by Giant Ventures, with participation from Y Combinator, Urban Innovation Fund, Collaborative Fund, Climate Capital, and angel investors; it also described the data-volume-based pricing model and early customers such as BMW.
Jobs and careers at Ohm
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