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Case Studies

Real deployments. Real numbers. No theoretical ROI — these are the outcomes our clients measured.

AI Agents Replacing a 6-Person Operations Team

BFSI — Global Financial Services

Agentic AILangGraphFastMCPFastAPI

Challenge

A chargeback processing team of 6 was handling disputes manually — slow turnaround, inconsistent decisions, zero audit trail. Compliance risk was mounting.

What We Built

Deployed a multi-agent system with LangGraph orchestrating stateful workflows. Agents reason through chargeback policies, call external tools via MCP servers, and escalate edge cases through human-in-the-loop review loops. Entire system exposed via FastAPI middleware integrated into existing infrastructure.

Business Impact

  • 35% improvement in processing accuracy
  • Replaced 6-person manual team entirely
  • Full audit trail — zero compliance escalations
  • End-to-end observability with LangSmith

Automated Document Intelligence for Financial Audits

BFSI — Audit & Compliance

VLMsOCRDocument AIPyTorch

Challenge

Teams manually extracting data from thousands of multilingual financial PDFs every month. Error-prone, slow, and impossible to scale during audit season.

What We Built

Built a Vision Language Model pipeline combining open-source VLMs with multilingual OCR on PyTorch. Documents go in, structured data comes out — audit-grade accuracy with zero human intervention. Integrated directly into the client's existing document management workflow.

Business Impact

  • 90%+ extraction accuracy on financial docs
  • Zero manual intervention in production
  • Multilingual support across document types
  • Scaled from 100s to 1000s of docs/month

Cutting LLM Inference Costs by 35% at Scale

Enterprise SaaS — Production AI Platform

vLLMLoRAQuantizationNVIDIA GPUs

Challenge

Production LLM inference was burning through cloud GPU budget. Throughput couldn't keep up with request volumes during peak hours.

What We Built

Fine-tuned domain-specific models (Qwen, DeepSeek) using LoRA and QLoRA on AWS SageMaker. Applied GPTQ and AWQ quantization. Deployed vLLM inference on mixed GPU/CPU infrastructure with optimized batching, parallelism, and KV cache tuning.

Business Impact

  • 3x throughput improvement
  • 35% inference cost reduction
  • 40% smaller model footprint
  • Zero accuracy degradation

Computer Vision Automating Retail Quality Control

Retail — Multi-Location Operations

YOLOv8OpenCVComputer VisionSageMaker

Challenge

Manual quality inspections across retail locations were inconsistent, slow, and couldn't keep up with growing product volume.

What We Built

Built computer vision pipelines with YOLOv8 for real-time object detection and OpenCV for preprocessing. Integrated directly into inventory management and quality inspection systems. Fine-tuned Stable Diffusion models for domain-specific visual tasks.

Business Impact

  • 92%+ detection accuracy
  • 40% reduction in manual inspection time
  • Real-time detection at production scale
  • Deployed across multiple retail locations

Data Platform Processing Millions of Records Daily

Enterprise — Data Infrastructure

SparkAirflowKafkadbtPower BI

Challenge

Fragmented data sources, broken pipelines, and data quality issues crippling downstream analytics and business intelligence.

What We Built

Architected end-to-end data infrastructure — scalable ETL/ELT pipelines with Python, SQL, and Spark. Star and snowflake schema design. Automated orchestration with Airflow, Kafka, and dbt. Power BI dashboards surfacing actionable insights in real-time.

Business Impact

  • 15% faster pipeline processing
  • 20% reduction in data incidents
  • Millions of records processed daily
  • Real-time dashboards driving decisions

Your business could be next

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