Most AI projects die in the gap between a promising proof of concept and a stable production system. We close that gap — from data architecture through inference serving, monitoring and retraining pipelines.
Our team ships models for finance, CPG, logistics, healthcare, retail and research use cases: demand forecasting, churn prediction, fraud detection, route optimization, visual inspection, OCR and customer intelligence. Every engagement ends with documented APIs, runbooks and handoff training — not just a model file.
Custom GPT-4o / Claude / Gemini fine-tunes, RAG pipelines, tool-calling agents and multi-agent orchestration with LangChain or LlamaIndex.
Time-series forecasting (ARIMA, Prophet, TFT), demand prediction, churn models, CLV scoring. Ensemble methods for volatile markets.
Detection, recognition, identification, OCR, automated counting, defect inspection, grading, visual database tagging and event monitoring from images or video.
Entity extraction, classification, sentiment, summarization and structured data extraction from unstructured documents at scale.
Feature stores, model registries, A/B experimentation, drift detection, automated retraining pipelines and compliance-grade audit logs.
Model quantization, ONNX export, TensorRT optimization and deployment to mobile, IoT devices and on-prem hardware.
Ensemble ARIMA + gradient boosting model for Patanjali. 4-week MAPE window, −18% hedging cost, 3× faster planning cycle.
Read case study → Research · DERAG-based support agent for Statista. 84% containment rate, −71% avg. handle time, multilingual (EN/DE/FR).
Read case study →