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AI & Automation Solutions

Intelligent systems that automate decisions, process documents, and scale operations

What Are AI & Automation Solutions?

AI and automation solutions use machine learning, natural language processing, and intelligent workflow orchestration to handle tasks that traditionally require human judgment — reading documents, making routine decisions, detecting anomalies, and predicting outcomes. Unlike simple rule-based automation, AI systems learn from data and improve over time.

At Mazwelt, we build AI systems that solve real business problems — not AI for the sake of AI. Every solution we build starts with a clear business case, measurable success criteria, and an honest assessment of whether AI is the right tool for the job.

What's Included

Every AI & automation engagement includes:

  • Process assessment — evaluating which processes benefit from AI vs. simpler automation
  • Data audit — assessing data availability, quality, and readiness for model training
  • Model development — building, training, and validating AI models on your data
  • Integration engineering — connecting AI capabilities to your existing systems via APIs
  • Confidence scoring — human-in-the-loop workflows for low-confidence predictions
  • Production infrastructure — model serving, scaling, and monitoring in production
  • Drift detection — automated monitoring for accuracy degradation over time
  • Documentation — model cards, API docs, and operational guides for your team

Capabilities

Intelligent Document Processing

Extract structured data from invoices, contracts, forms, tender documents, and reports — with 95%+ accuracy on well-defined document types. Supports multiple Indian languages and handwritten text recognition.

Predictive Analytics

Forecast demand, customer churn, equipment failures, and business outcomes using historical data. Deployed as dashboards, alerts, or automated decision triggers integrated into your existing workflows.

Decision Automation

Automate routine decisions — claim approvals, ticket routing, compliance checks, lead scoring — using ML models trained on your historical decision data. Reduces processing time from days to seconds for routine cases.

LLM & Generative AI

Build RAG (Retrieval-Augmented Generation) pipelines that ground language model outputs in your enterprise data. Conversational AI, document generation, summarisation, and intelligent search — with guardrails for accuracy and data privacy.

Pricing

  • AI Proof of Concept: ₹8–15 lakhs (4–6 weeks)
  • Single AI Capability (Production): ₹15–35 lakhs (3–4 months)
  • Enterprise AI Platform: ₹50 lakhs – ₹1.5 crores (6–12 months)
  • LLM/RAG Integration: ₹15–40 lakhs (2–4 months)
  • Ongoing Model Maintenance: ₹2–5 lakhs/month

Why Choose Mazwelt for AI

Our AI work is grounded in production reality, not demo magic. We build our own AI-powered products — BidSarathi uses NLP to process government tender documents at scale — which means we understand the difference between a model that works in a notebook and a system that works in production. We bring that operational discipline to every AI engagement.

Who This Is For

Enterprises with high-volume manual processes that bottleneck operations

Financial services companies needing automated document processing and compliance checks

Government organisations seeking to automate procurement, citizen services, or regulatory workflows

Manufacturing companies wanting predictive maintenance and quality analytics

Companies exploring LLM and generative AI integration into existing products

Our Process

1

Problem Assessment

We evaluate your current process to determine where AI adds genuine value versus where simpler automation suffices. Not every problem needs AI — and we'll tell you when a rule-based system or workflow automation tool is the better answer.

2

Data Audit

AI systems are only as good as the data they learn from. We audit your available data — volume, quality, completeness, and relevance — to determine what's feasible and what data gaps need to be addressed before model development begins.

3

Model Development & Training

We develop and train AI models using your data — NLP models for document understanding, computer vision models for visual inspection, predictive models for forecasting, or LLM pipelines for generative tasks. Each model is validated against real-world test cases before integration.

4

System Integration

AI models are integrated into your existing workflows and systems via APIs. We build the infrastructure for model serving, monitoring, and fallback handling — ensuring the AI system degrades gracefully when it encounters edge cases rather than failing silently.

5

Monitoring & Iteration

We deploy monitoring that tracks model accuracy, drift, and business impact in production. As real-world data reveals edge cases and distribution shifts, we retrain and refine models to maintain accuracy over time.

Frequently Asked Questions

What types of AI solutions does Mazwelt build?

We build four main categories of AI solutions: (1) Intelligent Document Processing — extracting structured data from invoices, contracts, forms, and reports using NLP and OCR. (2) Predictive Analytics — forecasting demand, risk, maintenance needs, and customer behaviour. (3) Decision Automation — routing, classification, approval, and compliance checking using ML models. (4) LLM Integration — building RAG pipelines, conversational AI, and generative workflows using large language models.

How much do AI automation solutions cost?

A focused AI implementation (e.g., document processing for a single document type) typically costs ₹10–20 lakhs. Enterprise AI platforms with multiple models and integrations range from ₹30 lakhs to ₹1.5 crores. LLM/GenAI integration projects typically start from ₹15 lakhs. Costs include data preparation, model development, integration, testing, and deployment.

How long does it take to deploy an AI solution?

A proof-of-concept with real data typically takes 4–6 weeks. Production deployment of a single AI capability takes 3–4 months. Enterprise-wide AI transformation with multiple models and integrations takes 6–12 months. We recommend starting with a focused proof-of-concept to validate feasibility before committing to full implementation.

Do we need a large dataset to start with AI?

It depends on the approach. Custom model training typically requires hundreds to thousands of labelled examples. Transfer learning and fine-tuning of pre-trained models can work with smaller datasets. LLM-based approaches using RAG (Retrieval-Augmented Generation) can deliver value with existing document repositories. We assess your data situation during the discovery phase and recommend the most practical approach.

What about AI accuracy — how do you handle errors?

We design AI systems with confidence scoring and human-in-the-loop workflows. Low-confidence predictions are routed to human reviewers rather than acted on automatically. This ensures accuracy for high-stakes decisions while still automating the majority of routine cases. We also implement continuous monitoring to detect accuracy degradation over time.

Can Mazwelt integrate AI into our existing software?

Yes. Most of our AI work involves adding intelligence to existing systems rather than building from scratch. We integrate AI capabilities via APIs — your existing applications call our AI services for predictions, classifications, or document processing, and receive structured results they can act on.

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BengaluruMumbaiDelhi

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