AI & Automation

Intelligent Automation That Replaces Real Manual Work

We build AI-powered systems that actually work in production — from LLM copilots and document processing to predictive analytics and workflow automation.

LLM
Integrations
Python
ML Stack
Production
Proven
Trusted by
150+ clients
India
UK
US & Global
Free estimate

What are you building?

Tell us what you need — scope and estimate in 24 hours, free.

No commitment · 24-hour response

OpenAIAnthropic ClaudeLangChainRAG pipelinesVector databasesPineconeDocument extractionOCRFine-tuningWhisperGeminiOpenAIAnthropic ClaudeLangChainRAG pipelinesVector databasesPineconeDocument extractionOCRFine-tuningWhisperGemini
What We Build

AI & Automation Services

01
🤖

LLM Integrations

GPT-4, Claude, Gemini — RAG pipelines and copilot features.

02
💬

AI Chatbots

Context-aware assistants with knowledge base retrieval.

03
📄

Document Processing

OCR, extraction, classification, and data normalisation.

04
📊

Predictive Analytics

ML models for forecasting, churn, and anomaly detection.

05
🔄

Workflow Automation

Replace manual processes with event-driven automation.

06
👁️

Computer Vision

Image classification, object detection, and quality inspection.

Technical Depth

AI Capabilities

🤖

LangChain & LlamaIndex

RAG pipelines, vector stores, and agent orchestration.

🧠

Fine-Tuning

Domain-specific model fine-tuning on your proprietary data.

📄

Document Intelligence

Azure Document Intelligence, AWS Textract, and custom OCR.

🐍

ML Stack

PyTorch, scikit-learn, Hugging Face, and MLflow.

☁️

Model Serving

FastAPI, Triton, SageMaker, and Vertex AI inference.

📊

MLOps

MLflow experiment tracking, model versioning, and drift monitoring.

How We Work

AI Development Process

01

Problem Definition

Identify the specific manual task or decision to automate.

02

Data Assessment

Audit available data quality, quantity, and labelling needs.

03

Model Development

Baseline model, evaluation metrics, and iterative refinement.

04

Production Deploy

Model serving, monitoring, and feedback loop integration.

What you get
  • Figma design source files
  • Clean documented codebase
  • CI/CD pipeline
  • SEO and analytics setup
  • Performance report
Technology Stack

AI Tech Stack

LLM
OpenAI GPT-4ClaudeLangChainLlamaIndex
ML
PyTorchscikit-learnHugging FaceMLflow
Data
PineconepgvectorWeaviateElasticsearch
Serving
FastAPITritonSageMakerCloud Run
Case studies

Systems we've built

FinTech · Document extraction

Invoice data extraction — 94% accuracy

Replaced a 3-person data entry team extracting fields from supplier invoices. GPT-4o + validation pipeline processes 500 invoices/day with a human review queue for confidence <0.9.

GPT-4oPythonPostgreSQL
Legal · RAG knowledge base

Internal contract knowledge assistant

RAG pipeline over 10,000 legal contracts. Associates ask questions in plain English and get cited answers in seconds — replacing hours of manual search.

ClaudeLangChainPinecone
HealthTech · Triage automation

Patient intake triage pipeline

AI triage for a telehealth platform — classifying patient symptom descriptions into urgency tiers and routing to the correct specialist queue. Replaced manual admin review.

ClaudeFastAPIPostgreSQL
Why Choose Us

Why Digital Web Weaver for AI?

⚙️

Engineering First

We build AI features that work in prod, not just demos.

📊

Measurable ROI

Every AI project defined with measurable success metrics.

🔒

Data Privacy

On-premise or private cloud LLM options for sensitive data.

🔄

MLOps Included

Model monitoring, drift detection, and retraining pipelines.

★★★★★

Our invoice processing used to take three people 6 hours a day. Now one person reviews the edge cases the AI flags. The accuracy is better than what humans were achieving manually.

MR
Meera R.CFO · Trading Company · India
★★★★★

What I appreciated was their insistence on measuring accuracy before building. We defined 'success' first, built a PoC, and only proceeded when the numbers were there.

JL
James L.CTO · Legal Tech · UK
★★★★★

The AI triage feature they built is now one of our core product differentiators. It's not a bolted-on chatbot — it's integrated into every patient flow and the accuracy keeps improving.

SP
Shilpa P.CPO · HealthTech · India
FAQ

AI Development FAQ

For well-defined, repetitive tasks — yes. We scope realistically: pilot one process, measure ROI, then expand.
Options include private cloud LLMs, on-premise Ollama, fine-tuning with your data on isolated infrastructure, or using only anonymised data.
Retrieval-Augmented Generation — an LLM answers questions by searching your documents first, so answers are grounded in your actual data.
Prototype with measurable results: 3–6 weeks. Production system with monitoring and feedback loop: 2–4 months.
Let's automate

Ready to replace manual work with AI?

Free 1-hour discovery session. We'll map your process and tell you what's worth automating — and what's not.

Production AI, not demosAccuracy measured firstData privacy by design