AI & Automation

Overview

Our AI & Automation practice focuses on taking complex, manual processes and converting them into reliable, explainable, and auditable systems. We combine data engineering, machine learning, natural language understanding, and robotic process automation (RPA) with software engineering best practices and robust MLOps.

Enterprise-grade Sub-services

1. Document Intelligence & OCR Automation

We build end-to-end document pipelines: scanning, OCR, semantic parsing, field extraction, entity linking and validation. Our solutions support invoices, receipts, contracts, purchase orders and multi-language documents with high accuracy using a hybrid approach (deep-learning OCR + rules + heuristics). Built-in data validation and human-in-the-loop review ensure low error rates for production workloads.

Key outputs: structured CSV/JSON, validated fields, metadata, audit trail.

2. Conversational AI & Virtual Assistants

Customer support bots, internal knowledge assistants, and workflow-triggering chatbots that integrate with your CRM, ticketing systems and databases. We design multi-turn dialogues, context management, fallback strategies and escalation flows to human agents. Emphasis on privacy, token minimization, and enterprise integrations (OAuth, SAML, SCIM).

Platforms: Open-source LLMs, OpenAI APIs, Rasa, Dialogflow, or hybrid deployments depending on compliance needs.

3. Custom Machine Learning Models

Supervised & unsupervised models, time-series forecasting, classification and anomaly detection tuned to your dataset and KPIs. We follow rigorous model lifecycle steps — problem scoping, data exploration, feature engineering, model training, A/B testing and deployment with automated monitoring.

Deliverables: trained models with versioning, reproducible pipelines and performance SLAs.

4. RPA & Workflow Automation

Automate repetitive UI and API tasks using enterprise-grade RPA tools plus backend automation. We blend RPA with AI (document extraction, decision models) for hybrid automation. Our workflows include audit logs, retry logic, rate-limiting and secure credential storage.

Integrations: SAP, Oracle, web-UI automation, email systems, and REST APIs.

5. MLOps, Monitoring & Continuous Delivery

We deploy models with CI/CD, containerization, canary rollouts and automated performance/DR drift detection. Production features include logging, explainability hooks, model governance and rollback mechanisms so ML systems remain reliable at scale.

6. Predictive Analytics & Decision Support

Forecasting, churn models, risk scoring and optimization engines that feed dashboards and automated decision actions. We focus on business-impact metrics and measurable ROI — produce models that directly tie to revenue, cost-savings or operational KPIs.

Technology & Architecture

Typical technologies we use include: Python (TensorFlow/PyTorch/Scikit-learn), FastAPI/Flask for model endpoints, Docker/Kubernetes for container orchestration, Hugging Face transformers, PostgreSQL / NoSQL for metadata stores, Kafka for event streaming, and Prometheus/Grafana for monitoring. For sensitive data we offer on-prem / VPC deployments and secure data encryption in transit and at rest.

Benefits & Why Customers Choose Us

• Production-first approach — models and automations designed to run reliably at scale.
• End-to-end ownership — data pipeline, model development, deployment, and monitoring.
• Explainability & governance — audit logs, human-in-loop workflows and compliance controls.
• Business metrics oriented — ROI, throughput, error reduction measured and reported.

Selected Case Study

Invoice Processing for Global Payments Provider: We implemented a hybrid OCR + ML pipeline, producing structured invoice data with 98.2% field accuracy. The system integrated with client ERP, reduced manual processing time by 87% and paid for itself in under 4 months.

Frequently Asked Questions