ATIMIS
Our Work
Production systems, running at scale.
Key Metrics
The Constraint
Tournament chess players and coaches lose crucial learning opportunities because paper scoresheets stay forgotten in bags or require tedious, manual move-by-move re-entry into digital software.
The Failure Mode
Traditional chess platforms require digital games, leaving handwritten scoresheets difficult to analyze. Manual transcription is tedious, and raw engine evaluations often lack actionable explanations.
How does this help?
Kibitzz bridges over-the-board chess and digital analysis by converting handwritten scoresheets into validated games in under 8 seconds. It combines Stockfish analysis, AI-powered game insights, and progress tracking to help players understand critical moments, learn from mistakes, and improve over time.
Veritas
Enterprise RAG Evaluation & Verification Framework for Production LLM Systems
Key Metrics
The Constraint
Enterprise teams deploying RAG systems lacked a scientific, repeatable way to measure answer reliability. "Looks correct" was unacceptable in regulated and knowledge-critical environments.
The Failure Mode
Traditional RAG pipelines often retrieve incorrect context while still producing fluent responses. These silent hallucinations erode trust and introduce legal and compliance risk.
How does this help?
Most evaluation approaches collapse system behavior into a single score. In practice, failure occurs independently across retrieval, factual grounding, and reasoning. Measuring these dimensions without masking risk required a fundamentally different framework design.
Sentinel
Enterprise Material Request Governance and Compliance Platform
Key Metrics
The Constraint
Material requests operated under strict yearly and departmental limits. Any over-allocation created financial exposure and audit risk.
The Failure Mode
Manual approvals and spreadsheet-driven tracking allowed inconsistent enforcement, delayed detection, and policy violations.
How does this help?
The system required absolute enforcement: no warnings, no overrides, no partial approvals, while remaining fast and usable for daily internal operations.
DataVista
Real-Time Data Analytics & Visualization Platform for High-Volume Workloads
Key Metrics
The Constraint
Teams needed real-time insight from large datasets without adopting heavy BI platforms or complex infrastructure.
The Failure Mode
Batch-based reporting pipelines introduced delays, limiting decision-making speed and operational visibility.
How does this help?
Achieving real-time responsiveness while processing large-volume data required distributed computation without degrading frontend performance.
FitIQ
AI-Powered Fitness Coaching with Real-Time Form Tracking
Key Metrics
The Constraint
Users needed personalized fitness coaching without gym access, while maintaining correct form to reduce injury risk using standard consumer devices.
The Failure Mode
Static workout plans and delayed feedback led to incorrect execution, reduced results, and higher injury rates.
How does this help?
Real-time computer vision is computationally intensive. Delivering low-latency pose tracking and personalization without expensive hardware or constant cloud inference required deep optimization.
AutoSteer
High-Precision Steering Angle Prediction for Autonomous Driving Systems
Key Metrics
The Constraint
Autonomous driving systems require highly accurate, real-time steering predictions to maintain safety and lane stability.
The Failure Mode
Minor prediction errors compound rapidly, resulting in unstable trajectories and unsafe driving behavior.
How does this help?
Driving environments vary continuously: lighting, curvature, and obstacles change frame-to-frame. The model had to generalize while maintaining ultra-low latency.