Industries · Energy
AI for energy assets that runs on data you can trust.
We help startups building AI for plants, grids and energy infrastructure get their asset data live, clean and connected — so monitoring, anomaly detection and forecasting hold up where downtime is expensive and sites are remote.
Where energy AI gets stuck
The data exists. It's just scattered, remote and hard to trust.
Data scattered across systems
SCADA, historians, meters, vendor portals and spreadsheets — each with its own format and timestamps. Joining them is most of the work.
Remote sites, unreliable links
Wind farms, solar sites and substations lose connectivity. The product has to keep working offline and catch up cleanly when the link returns.
Data that can't leave the site
Operators are cautious about critical infrastructure data. Processing at the edge and sending only what's needed is often the only acceptable design.
Context changes everything
An output drop might be a fault — or just cloud cover, curtailment or planned maintenance. Without weather and operating context, anomaly alerts lose trust fast.
What we build
Physical AI products for plants, grids and energy assets.
Paranjay leads every engagement as your fractional Head of Data & AI, Product or Engineering. Our team builds alongside yours.
Asset monitoring & anomaly detection
Catch developing problems across turbines, inverters, batteries and substations — with alerts that account for weather and operating context.
Asset telemetry · Weather · Alarms
Predictive maintenance for energy assets
Plan maintenance before failures, built on the signals and maintenance history that matter for each asset type.
Sensor data · Work orders · Asset history
Forecasting
Forecast generation or demand by combining asset data with weather and historical patterns — and know how much to trust each forecast.
Meter data · Weather · Historical load
Site-to-cloud data platforms
Collect, clean and move data from remote sites on ready-made gateways and edge devices, keeping sensitive data on site where it has to stay.
SCADA · Edge · MQTT
Why it transfers
Remote devices, messy signals, huge scale.
Energy assets share the hardest data problems we've solved elsewhere: devices that go offline, signals that differ by vendor and model, high volumes and real-time needs. Our founder built a platform with 1M+ endpoints connected at once and 3+ enterprise data platforms — the same discipline applies to plants and grids.
How we work
Data first. Then AI.
01 — DIAGNOSE
Find the real problem
Two weeks with your team, your assets and your data. A written read on what to fix first — and what to ignore.
02 — BUILD
Ship it with you
Sprint by sprint, with a working demo each time: site-to-cloud pipelines, models that account for context, and edge processing where data must stay on site.
03 — PROVE
Measure the outcome
Judged on the outcome we named up front — a pilot that converts, downtime avoided, a platform ready for your next round.
Why Paranjay
15 years building data systems that had to work — including a platform with 1M+ endpoints connected at once.
Read Paranjay's story →1M+
endpoints connected at once
3+
enterprise data platforms built
15+ yrs
Volkswagen, Nissan, Delivery Hero
3
countries: Germany, India, US
Related reading
Go deeper.
Edge or Cloud? A Founder's Guide for Physical AI Products →
Every physical AI startup hits the same question: should the AI run on the device or in the cloud? The honest answer is usually 'both' — here's a plain-language way to decide what goes where.
Why Your Physical AI Demo Works in the Lab and Fails in the Field →
The demo worked on your test data. On a real customer's machines, it falls apart. It's rarely the model's fault — it's the gap between lab data and field data. Here are the five gaps we see most, and how to close them.
How to Scope a Predictive Maintenance Pilot That Converts to Paid →
Most physical AI pilots end with a polite 'interesting, let's stay in touch'. The ones that convert are scoped differently from day one. Here's how to design a pilot your customer can say yes to.
Common questions
Questions founders ask us.
Your next step
Building AI for machines, vehicles or energy? Let's talk.
Tell us what you're building and where it's stuck. Paranjay replies personally within 1 business day with a first read on where to focus. No pitch. No pressure.
or email hello@getrightshift.com