Batteries bring the flexibility modern grids depend on. We ensure they scale profitably.

Amperical makes BESS intelligence accessible, so assets scale up profitably. AI agents bring efficiency; domain experts bring judgment.

For The BESS Ecosystem

  • Developers
  • Owners
  • Operators
  • Financiers
  • Insurers

Across every US ISO

  • ERCOT
  • CAISO
  • PJM
  • MISO
  • NYISO
  • SPP
  • ISO-NE
Amperical Teammates simulated replay
Example use case 1 · Operations

AIReliability EngineerAvoided a repeat $270k shortfall

Caught PCS heat derating before tomorrow's day-ahead offer
  1. AISCADA OperatorDetects reduced PCS outputautomatic
  2. AIReliability EngineerForecasts tomorrow's heat limitautomatic
  3. Asset managerApproves the limithuman approval
  4. AIDispatch OptimizerRevises the offer for the QSEautomatic
Dispatch vs PCS limit · MW Discharge Charge PCS limit 3001500−150 180 MWh short cost $270k offer capped at 100 MW delivered in full Day 1 · heat fault Day 2 · revised offer result: $270k repeat loss avoided
Simulated replay of a 300 MW site. Cost assumes the shortfall is bought back at $1,500/MWh

Outcomes

Higher revenue, lower operating and engineering costs

Team productivity

Workflow automations

Example tasks

  • Reference engineering specs or regulations
  • Generate reports and presentations

Saves engineering cost

Asset performance

Reduced downtime and losses

Example tasks

  • Continuous monitoring
  • Running timely data models autonomously
  • Resolving alerts and errors

Saves cost of operations

Revenue optimization

Dispatch diagnostics and optimizations

Example tasks

  • Diagnose lost bids
  • Customize bids in response to battery conditions

Improves revenue

Amperical Teammates

Agents roster

Each type of task has a dedicated agent with its own tooling and domain knowledge

Agents at work

Example use case 2 · Procurement

AIProcurement AnalystFound a bid $9.6M cheaper over 20 years

Compared five OEM bids for 300 MW / 1,200 MWh on lifetime cost
  1. AIProcurement AnalystNormalizes scope and usable capacityautomatic
  2. Project engineerApproves cycles and assumptionshuman approval
  3. AIReliability EngineerModels degradation and augmentationautomatic
  4. AIProcurement AnalystRanks bids by 20-year cost NPVautomatic
20-year cost NPV · $/kWh at POI $234Bidder C$242Bidder D$244Bidder E$249Bidder A$364Bidder B lowest lifetime cost lowest quote, no tax credit result: $9.6M below the next-best bid
Illustrative bids, 8% discount rate. Tax-credit eligibility to be verified
Example use case 3 · Siting

AIEnergy Market AnalystShortlisted a site with $18M/yr spread potential

Screened West Texas nodes near data centers and 345 kV lines
  1. AIEnergy Market AnalystMaps load, generation and transmissionautomatic
  2. AIEnergy Market AnalystRanks nodes by TB4 spreadautomatic
  3. DeveloperApproves the site for studyhuman approval
  4. AIDispatch OptimizerModels revenue and sizes the batteryautomatic
Data center Generator Planned BESS 345 kV data center · 2.1 GWdata center · 1.8 GWdata center · 2.0 GW 20 km Candidate BESS site result: node TB4 median $42/MWh
Illustrative site. $42/MWh TB4 × 1,200 MWh × 365, before losses.

How It Works

BESS-native AI harness

Where we fit

One team of BESS-native agents replaces three kinds of tools.

How Amperical agents replace other tool types
Other toolsAmperical agents
General-purpose AIGeneric research and writing
BESS-native AIGrounded in your data and engineering models
BESS analyticsMonitors and flags issues
Issue resolutionDiagnoses root causes and prepares fixes
Dispatch optimizersOptimizes market offers
Constraint-aware dispatchOptimizes dispatch within BESS constraints
Amperical harness: customer telemetry, location, design and specs flow through BESS tools and AI agents to produce actionable intelligence

How the harness works

Your data, BESS tools, expert approval

Project context
Telemetry, design, specs and location
→
BESS tools
Engineering models and market data
→
Expert approval
Domain experts + engineering guardrails

Team

Combining deep energy + AI expertise

Rachana Vidhi, PhD

Co-founder & President

  • 10 US patents in batteries and renewables enabling 1,000MW+ of BESS deployments
  • PhD Chemical Engineering (USF), Master's in Management (Harvard), IIT Kharagpur
  • Former Director, NextEra Energy
Rachana in Florida Inventors Hall of Fame →

Indresh Kumar

Co-founder & CEO

  • Pioneered BESS analytics at Ion Energy: Amazon backed, scaled to 600MWh+ AUM
  • Developed battery fleet operations AI/ML models at VoltUp
  • Technical co-founder: AI, ML and data models
Indresh on ~600MWh BESS analytics in California →