Make the right shift.
Data first.
Then AI.
AI is only as good as the data it runs on. Rightshift is the Data & AI team for physical AI startups: we get your machine, vehicle and sensor data live, clean and right — so your AI works the way it should.
Paranjay Menaria
Founder · Data & AI
1M+
Endpoints connected
at once
3+
Enterprise data
platforms built
Free 30-min call. You leave with a first read on your data, even if we never work together.
We built an AI diagnostics assistant for field technicians
Sensor data, service history and manuals in. The likely fault and next steps out.
5 mo
idea → live MVP
3
customer pilots running
1
pilot converted to paid
1 → 7
team scaled with scope
How it reads one CNC spindle: data first, then the answer
Example
Spindle vibration
7.8 mm/s · 2.6× baseline
Bearing temperature
71 °C · +18 °C
Similar past tickets
412 · matched
Spindle load
64 % · normal
Likely fault: front spindle bearing wear
Built data systems at
CARIAD · Volkswagen Group
Nissan Motors
Delivery Hero
Who this is for
Startups building AI for machines, vehicles and energy.
Physical AI is our niche because the data is the hard part: messy, high-volume, coming from devices in the field. That's the problem our founder spent 15 years solving.
Manufacturing
Diagnostics, predictive maintenance and quality inspection for the machines that keep factories running.
Machine logs · vibration · PLC data · service records
Mobility
Fleet intelligence, vehicle health and telematics products built on data from cars, trucks and fleets.
Vehicle signals · GPS · CAN bus · trip data
Energy
Monitoring and forecasting for plants, grids and infrastructure — where downtime is expensive and data is scattered.
SCADA · meter data · weather · asset telemetry
You're a non-technical founder
You know the customer and the workflow better than anyone. You need someone senior to own the technical calls, explain them plainly, and get a working product in front of customers.
→ We step in as your fractional CPO, CTO or Head of Data & AI.
You're a CTO who needs depth
Your team ships software well, but device data and AI at scale are new territory. You want a senior partner and extra builders — without losing control of your stack.
→ We join your team as a Data & AI partner. You stay in charge.
Not a pitch — a working example
An AI that tells a field technician what's broken before they open the panel.
A simplified version of the diagnostics assistant we built for an industrial AI startup. Pick a machine, describe the fault, and watch it reason over service history and sensor data.
Machine
Live sensor snapshot
~3 seconds.
Why physical AI stalls
Building the model is the easy part. Making it work on real-world data is where startups get stuck.
“The demo worked on our test data. On a real customer's machines it falls apart.”
Field data is noisy, incomplete and different at every site. Models trained on clean samples break on contact.
“I don't know if our data is good enough for AI — or what we should even be collecting.”
Most physical AI startups collect too little of the right signal and too much of the wrong one. That gets expensive to fix later.
“Every engineer I talk to suggests a different stack. I can't tell who's right.”
Edge or cloud, build or buy, which model, which hardware. Without senior judgment, every choice is a guess.
“Investors keep asking what our moat is.”
In physical AI, the moat is proprietary real-world data, collected reliably at scale. Few startups can show that yet.
The problem usually isn't effort. It's missing someone who has done this at scale before.
Track record
Fifteen years of data systems that had to work — across vehicles, marketplaces and manufacturing.
15+
years building, managing and scaling data systems
1M+
endpoints connected at once on one platform
3+
enterprise data platforms built from scratch
3
countries worked in: Germany, India, US
CARIAD · Volkswagen Group
Vehicle data collection platform
Owned data collection across the US, Europe and China: 1M+ endpoints connected at once, petabytes of data a day, ingested, processed in real time and stored.
Mobility · Real-time data
Delivery Hero
Data platform at global scale
Built the data platform for one of the world's largest food delivery companies, in Germany.
Marketplace · Data platform
Nissan Motors
ML inventory optimization
Built machine-learning inventory optimization on real inventory data, not lab samples.
Manufacturing · Applied ML
How we work
Senior judgment up front. A team that ships behind it.
Every engagement is led by Paranjay personally, and our team does the build. You get senior judgment on every call that's expensive to get wrong.
01 — DIAGNOSE
Find the real problem
Two weeks with your team, your devices and your data. You get a written read on what to fix first — and what to ignore.
- Audit of what your devices collect, and what's missing
- Edge vs. cloud, build vs. buy, which hardware
- A named outcome and how we'll measure it
02 — BUILD
Ship it with you
Paranjay stays in the seat as your fractional CDO, CPO or CTO. Our team builds alongside yours, sprint by sprint, with a working demo each time.
- Device-to-cloud data pipelines
- AI models that hold up on field data
- Integration with ready-made sensors & edge devices
03 — PROVE
Measure against the outcome
We judge the work by the outcome we named in week two: a live pilot, a converted customer, a platform ready for your Series A.
- Baseline vs. result, in numbers
- You own all code, models & IP
- Clean handover or ongoing leadership
The stack we build physical AI on — from the device to the model
Edge & devices
Streaming
Storage
Processing
AI & ML
Cloud & ops
What we do
Senior leadership when you need direction. Delivery when you need it built.
Lead
Fractional leadership, part-time, from week one
FRACTIONAL CDO
Head of Data & AIMOST COMMON START
What to collect, how to move it, which AI to build on it.
→
FRACTIONAL CPO
Head of Product
Industry knowledge into a product customers pay for.
→
FRACTIONAL CTO
Head of Engineering
Architecture, first hires and a delivery rhythm.
→
Solve
A defined problem, one named outcome, our team to deliver it
2 WEEKS
Data & AI Diagnostic
A written plan on what to fix first, and what to ignore.
→
DATA
Device-to-Cloud Data Platforms
Reliable data from machines, vehicles and sensors.
→
AI
Physical AI Products
Diagnostics, predictive maintenance, fleet intelligence.
→
Why Rightshift
Most fractional CTOs come from web software. Our founder built data platforms for 1M+ connected devices.
Here's how we compare with what founders usually consider first.
Hire a full-time CTO
3–6 months to hire, a big salary and equity, and a wrong hire is costly.
✓ Senior leadership from week one, part-time.
A dev agency
Builds to spec. If you can't write the spec, you get the wrong product.
✓ We shape the product with you, then build it.
An AI consultancy
Priced and paced for enterprises.
✓ Startup pace, startup scope.
Freelance ML engineers
Execution without strategy. You still make every hard call.
✓ A senior leader owns the calls with you.
A typical fractional CTO
Usually a web or SaaS background — not machines, vehicles or sensors.
✓ 15 years in data systems; 1M+ endpoints connected at once.
Case study
What founder-led looks like in practice.
Industrial AI · Equipment maintenance & field service · India & US
From idea to an AI product customers are piloting — in 5 months.
An early-stage industrial AI startup needed an AI diagnostics assistant, an expert knowledge base and a live operations dashboard for the technicians who keep machines running. Paranjay stepped in as fractional CPO, shaped the product with the founding CTO, and scaled our team from one engineer to seven as the scope grew. Ten sprints later, the MVP was live with real customers.
5 mo
idea to live MVP
3
customer pilots running
1
pilot already converted to paid
1 → 7
team scaled with scope
The person behind Rightshift
Every engagement is led by Paranjay Menaria.
15 years building data systems at Volkswagen Group, Nissan and Delivery Hero. He started Rightshift because physical AI startups hit the same data problems — years before they can afford to hire someone who has seen them.
Common questions
Questions founders ask us most.
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