Research & Development Platform

Micantis helps you scale from research lab to commercial production

Accelerate Battery Innovation

Built for battery startups and R&D teams developing breakthrough technologies with commercial ambitions.

From prototype cell development to pilot production scaling, Micantis eliminates data bottlenecks so you can focus on innovation, not spreadsheets. We grow with you from first proof-of-concept through commercial manufacturing.

Battery Data Analysis Platform

Works With Your Lab Equipment

Seamless data import from all major battery testing equipment

Battery Cyclers

We guarantee data import from any cycler - if we don't support yours yet, we'll add it

Potentiostats & EIS

Import EIS data and electrochemical measurements

LIMS Systems

Connect lab data with sample tracking and metadata

Comprehensive R&D Platform Features

One-Click Data Analysis

From raw data to insights in seconds

Stop wrestling with Excel and complex Python scripts. Get instant, professional visualizations of your battery data with one click. Focus on developing better batteries, not better spreadsheets.

  • One-click visualizations: Voltage curves, capacity fade, dQ/dV, EIS Nyquist plots
  • Multi-cell comparisons: Overlay unlimited datasets for comprehensive analysis
  • Interactive exploration: Zoom, pan, and inspect individual data points
  • Professional quality: Clean, presentation-ready visualizations
  • Smart annotations: Add context and insights directly to your graphs
Advanced Battery Data Graphing

Interactive graphing with multiple datasets and professional styling

Custom Research Dashboards

Build personalized views for your research

Create custom dashboards that show exactly what matters for your specific research goals. Monitor live experiments, compare test campaigns, and share insights with your team.

  • Drag-and-drop builder: Create dashboards without any coding required
  • Real-time updates: Live data streaming from running experiments
  • Multi-experiment views: Compare results across different test campaigns
  • Shareable templates: Standardize dashboard views across research teams
  • Mobile responsive: Monitor experiments from anywhere, anytime
Custom Research Dashboards

Customizable dashboards with real-time experiment monitoring

Advanced Electrochemical Analysis

Automatic feature extraction from complex electrochemical data

Skip the manual data processing. Micantis automatically extracts key parameters from EIS, HPPC, and other electrochemical tests, giving you instant insights into battery performance and degradation mechanisms.

  • EIS analysis: Automatic Nyquist/Bode plots with circuit fitting
  • HPPC processing: Resistance extraction and power capability mapping
  • Feature extraction: Automated parameter calculation and trending
  • Multi-condition analysis: Temperature and SOC correlation
  • Degradation tracking: Automated detection of performance changes
  • Mechanism identification: Pattern recognition for failure modes
EIS Analysis Tools

Advanced EIS analysis with automatic circuit fitting

HPPC Power Analysis

HPPC analysis with automated resistance and power extraction

Developer APIs & Integration

Seamless integration with your existing workflows

Integrate Micantis into your research ecosystem with comprehensive APIs and SDKs. Whether you're using Jupyter notebooks, custom scripts, or automated pipelines, Micantis fits into your workflow.

  • Python SDK: Native Jupyter notebook integration for data scientists
  • REST API: Full platform access for custom applications
  • Real-time streaming: Live data WebSocket connections
  • Batch processing: Efficient bulk data operations
  • Custom algorithms: Deploy your models on our infrastructure
Python SDK Example
import pandas as pd
from micantis import MicantisAPI

# Connect to Micantis platform
api = MicantisAPI(service_url=SERVICE_URL, 
                  username=USERNAME, 
                  password=PASSWORD)
api.authenticate()

# Get cell data and metadata
cells = api.get_cells_list(search="*LFP*")
data_table = api.get_data_table(search="cycle_life", limit=100)

# Download test data
file_ids = data_table['id'].to_list()
test_data = []
for file_id in file_ids:
    df = api.download_csv_file(file_id)
    test_data.append(df)

# Combine and analyze
all_data = pd.concat(test_data)
print(f"Analyzed {len(test_data)} test files")

Streamline Your Research Workflow

Import

Automatic data collection from 50+ cycler formats

Process

AI-powered feature extraction and analysis

Visualize

Interactive graphs and custom dashboards

Collaborate

Share insights with your team instantly

Choose Your Plan

Scale from research to production with flexible pricing

Basics

Perfect for individual researchers and small labs

Core analysis tools
Basic graphing & visualization
Data import from major cyclers
5 users included
Email support

Enterprise

For production-scale operations

Everything in Professional
On-premise deployment
Custom integrations
Unlimited users
Dedicated support manager
Training & consulting

Accelerate Your Battery Research Today

Join leading research institutions and companies using Micantis.

Request Demo