Applied Machine Learning & Custom LLM Engineering

Applied Artificial Intelligence & Custom ML Solutions

Harness real, practical AI without the buzzwords. We build private knowledge assistants (RAG), intelligent document parsing pipelines, and predictive machine learning models integrated directly into your existing business software.

100% Private (Zero Data Leaks) Intelligent PDF OCR Parsing Strict Token & Cost Guardrails Predictive Churn & Lead Scoring
Enterprise AI Safeguards SECURE RAG
Private Vector Database (Chroma / Pinecone)
Zero model training on your proprietary data
Semantic caching to reduce API costs by up to 70%
Strict output validation to eliminate hallucinations
Full GDPR and data protection compliance.
Real Challenges Addressed

Where Businesses Struggle With AI

Implementing AI without proper engineering leads to high cloud bills, data leaks, and inaccurate answers.

Data Leakage to Public Models

Employees pasting private contracts and financial spreadsheets into public web AI tools, risking catastrophic data leaks.

Costly AI Hallucinations

Generic AI chatbots making up false product prices, incorrect return policies, and inaccurate facts to customers.

Manual PDF & Invoice Reading

Accounts staff spending 25+ hours every week manually opening vendor invoices and typing line items into accounting software.

Unpredictable Cloud API Bills

Unoptimized LLM prompts without token caching racking up unexpected thousands of dollars on monthly cloud API bills.

Repetitive Support Overload

Support staff answering the exact same 30 technical questions instead of focusing on high-ticket customer success.

No Predictive Capabilities

Treating all inbound sales leads equally instead of using machine learning algorithms to prioritize high-value prospects.

Practical AI Engineering

Features & Business Outcomes

We build production-ready AI pipelines designed for real-world business accuracy, speed, and affordability.

Private RAG Knowledge Bots

AI assistant trained exclusively on your internal SOPs, product manuals, and policies. Provides grounded answers with citations.

Benefit: Zero Hallucinations
Intelligent Document Extraction

Automatically ingest PDF invoices, shipping bills, and receipts, extracting line items, GST numbers, and totals directly into database tables.

Benefit: 95% Faster Invoice Processing
Predictive Lead Scoring

Machine learning algorithms trained on your past sales records to score new inquiries and rank them by conversion probability.

Benefit: Focus Sales on Closing Deals
Zero Data Leakage Guardrails

Enterprise privacy agreements and on-premise embeddings ensure your customer and financial records are never used to train public models.

Benefit: 100% IP & Data Protection
Semantic Caching & Cost Control

Intelligent caching stores answers to recurring questions in vector memory, reducing third-party cloud API costs by up to 70%.

Benefit: Predictable, Low Cloud Bills
REST API Integration

Deploy your trained models and LLM chains as secure REST endpoints ready to connect to your existing website, CRM, or POS software.

Benefit: Works with Your Current Tools
Modern AI Stack

Technologies We Use

We leverage industry-standard AI libraries, state-of-the-art LLMs, and vector stores.

Python
PyTorch & Scikit-Learn
OpenAI / Claude
Advanced LLM reasoning
Chroma / Pinecone
Vector database retrieval
LangChain
RAG pipeline orchestration
Tesseract & OCR
Document parsing engines
FastAPI & Docker
High-speed model serving
Real-World AI

Featured AI Deployments

Explore concrete implementations delivering tangible time savings and prediction accuracy.

DOCUMENT INTELLIGENCE

Automated Invoice & Receipt Parser

AI OCR microservice that parses vendor PDF invoices, extracts vendor name, GST number, line-item totals, and posts directly to accounting database.

Accuracy: 99.2% extraction precision.
Turnaround: Parses 10-page PDF in 1.8s.
Tech: Python, OCR, Claude API.
ENTERPRISE KNOWLEDGE

Private Internal Handbook RAG Bot

Internal company assistant embedded in team Slack that searches across 350+ pages of product specs, HR policies, and guides to answer employee questions instantly.

Zero Hallucinations: Cites exact page numbers.
Security: Self-hosted Chroma vector database.
Support: Cut internal query tickets by 65%.
PREDICTIVE ANALYTICS

Lead Scoring & Churn Classifier

Scikit-Learn random forest classifier analyzing user engagement patterns across 20,000 historical accounts to flag customers likely to churn 30 days before cancellation.

Recall: 87% accuracy on churn detection.
Automation: Triggers retention email & discount.
Impact: Saved estimated ₹12 Lakhs annual MRR.
FAQs

Frequently Asked Questions

Key questions regarding AI privacy, costs, and integration feasibility.

Will our company data be used to train OpenAI or other public models?
No, never. We use enterprise API tiers (OpenAI, Anthropic, Google Cloud) that explicitly state in their terms of service that API inputs and outputs are never used to train future models. Furthermore, your embeddings and documents live in your own private vector database.
How do you prevent the AI from making up false answers (hallucinations)?
We implement strict Retrieval-Augmented Generation (RAG) with semantic guardrails. The AI is explicitly instructed to only answer using provided document excerpts. If the information does not exist in your verified documentation, it responds truthfully: "I do not have sufficient information in the verified records to answer this question."
What are the ongoing cloud API costs of running these models?
Because of modern token optimizations and semantic caching, ongoing API costs for small-to-midsize businesses typically range from just $5 to $35 per month. We set hard monthly budget caps to ensure you never experience unexpected billing surprises.
Can the AI bot connect to our live CRM or database to take actions?
Yes! We can equip your AI agent with Function Calling / Tool Use, allowing it to look up order statuses in your SQL database, generate PDF invoices, or update lead contact records in your CRM securely.
How long does it take to deploy an AI document or RAG bot?
A standard document parser or private knowledge RAG assistant typically takes 2 to 3 weeks from initial document ingestion and embedding to production deployment.
Send Project Requirements

Send Your AI Project Requirements & Get a Free Feasibility Roadmap

Tell us about your document workflows, repetitive inquiries, or predictive scoring goals. Lead AI engineer Sanjay will review technical feasibility and provide an honest roadmap with cost projections within 24 hours.

Mutual NDA & Data Security Your documents and proprietary processes are 100% confidential.
Milestone-Based Delivery Prototype validation before full production scaling.
Direct WhatsApp Collaboration Work directly with lead engineer Sanjay.
Chat on WhatsApp Directly

Strictly confidential. Mutual NDAs signed upon request.