The Mitra Chem Acceleration Platform

Mitra Chem's full-stack AI platform enables faster, better, and cheaper design for manufacturing - from lab synthesis to factory scale-up.

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AI Agents
Specialized ML
Design Studio
Data Infrastructure
Physical Layer

AI Agents

Specialized agents for R&D, Process Engineering, and Software Development working alongside engineers and by themselves.

Sparky

Sparky

AI Data Scientist

Researcher Zero

Researcher Zero

AI Research Scientist

Swefan

Swefan

AI Software Engineer

Pierre

Pierre

AI Code Reviewer

01 / 05 Collect
SEM · Raw image
SEM raw
Segment · Boundaries
SEM segmented
312 particles
primary
Primary
secondary
Secondary
Morphology
Ellipticity
Circularity
Roughness
Feret Dia.
Particle Size Distribution
Real-time calcination telemetry
Mitra Chem pilot line and lab
Meet our Agents

AI that works alongside our engineers

Specialized agents handle R&D questions, code reviews, and build software.

Sparky

AI Data Scientist

Domain-aware AI assistant used by every engineer daily, directly consuming Mitra Chem's data and codebases for analysis, process insights, and R&D questions.

Swefan

AI Software Engineer

Autonomously takes feature requests and bug reports to completed PRs.

org/data-pipeline Pull Request
✓Add batch retry logic to ingestion pipeline#287
ai-agent opened this pull request 3 minutes ago
CI / tests (14/14 passed)
Pierre / security review
Pierre / architecture review
Ready to merge 3 files changed, +47 -12

Pierre

AI Code Reviewer

Three parallel review agents analyze every pull request and self-improve weekly.

S Mitra Chem #eng-code-reviews
Pierre
PierreAPP10:42 AM
✅ Pierre approved: org/frontend#142
Dashboard refresh: update chart components and fix layout
✓Merged2 min ago
3 agents ran: Security ✅ Correctness ✅ Architecture ✅
Pierre
PierreAPP10:43 AM
Weekly self-improvement: reviewed 47 disagreements, updated 3 review rules
Researcher Zero

AI that works by itself

A long-horizon, multi-agent research system with persistent agent memory. Each analysis compounds institutional knowledge, making the next one smarter.

HypothesizeGenerate questions based on all relevant context
AnalyzeStatistics, ML, and physics-based models
VerifyMulti-method consensus and cross-ref
LearnUpdate hypothesis and suggest next experiments
DocumentWeekly report and knowledge base update
Researcher Zero
80%
Reduction in R&D analysis time
15-20
Hypothesis cycles per run
Multi-hour
Autonomous sessions
Multi-month
Context retention

See the platform in action.

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