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AI & ML Development

Production-Ready AI & Machine Learning Systems

We design, build and deploy AI and machine learning solutions that work with your data, software and business systems, from intelligent applications to production ML platforms.

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From data signals to a production modelDocuments, images and event data feed one model, which produces a resolved result inside a running product, monitored and retrained underneath.DOCUMENTSIMAGESEVENTS & DATAMODELLLM · ML · CVIN PRODUCTIONMONITORED & RETRAINED
Inputs · Model · Production

Start with the outcome

What Are You Trying to Achieve?

Start with what you need AI to do. We’ll help identify the right capability and the engineering needed to put it into use.

Pick what you’re trying to do

You picked

Create an AI Assistant

Give employees or customers intelligent access to business knowledge, documents and information.

What we could build
What you could create
  • An internal assistant that answers from your own policies, contracts and documentation
  • A customer-facing assistant that resolves routine questions without a handover
  • A search layer that returns an answer with the source document attached
What it works with
  • Document stores, wikis and shared drives
  • The permissions your teams already have
  • Support or CRM history, where it exists
Best fitGenerative AI & LLMs
Connected engineering
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You picked

Put AI to Work Across Your Business

Use AI agents to reason, interact with systems and complete multi-step tasks.

What we could build
What you could create
  • An agent that completes a multi-step process end to end and reports what it did
  • A review step where the agent proposes and a person approves
  • Agents that read from and write to the systems your teams already use
What it works with
  • APIs on your ERP, CRM or ticketing systems
  • A defined boundary for what the agent may decide alone
  • An audit trail of every action taken
Best fitAI Agents
Connected engineering
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You picked

Predict What Happens Next

Use business data to forecast demand, risk, customer behaviour, failures and opportunities.

What we could build
What you could create
  • Demand and capacity forecasts your planners can act on each week
  • Risk, churn and propensity scores delivered into the tools where decisions are made
  • Early warning on failures, delays and anomalies
What it works with
  • Two to three years of historical records
  • One outcome the business already measures
  • A place for the score to land — a screen, a queue or a rule
Best fitMachine Learning
Connected engineering
Send this brief to our AI team Talk to our AI team instead
You picked

Understand Images, Video or Documents

Extract meaning, identify patterns and automate decisions from visual information.

What we could build
What you could create
  • Automated inspection that flags a defect before it travels downstream
  • Document and invoice extraction that posts straight into your systems
  • Video analytics for safety, compliance or movement
What it works with
  • Samples that are labelled, or that can be
  • Camera, scanner or drawing feeds
  • Somewhere to run it — edge device or cloud
Best fitComputer Vision
Connected engineering
Send this brief to our AI team Talk to our AI team instead
You picked

Automate Repetitive Work

Combine AI, workflows and business rules to reduce manual effort across operations.

What we could build
What you could create
  • A queue that clears itself, with exceptions routed to a person
  • Document-to-system flows that remove manual re-entry
  • Business rules and AI running in one path instead of two
What it works with
  • The process as it actually runs, not as it is documented
  • System access or APIs at each step
  • A named owner for the exceptions
Best fitIntelligent Automation
Connected engineering
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You picked

Take AI Into Production

Put the infrastructure, monitoring, governance and engineering in place to operate AI reliably at scale.

What we could build
What you could create
  • A deployment path that ships a model change without rebuilding the product
  • Monitoring for drift, cost and quality, with alerts that mean something
  • Evaluation, governance and rollback you can show an auditor
What it works with
  • A model or prototype that already works
  • Your cloud or on-premise platform
  • Owners for accuracy, cost and uptime
Best fitAI Engineering & MLOps
Connected engineering
Send this brief to our AI team Talk to our AI team instead

Not sure where to start? Talk to our AI team

AI & ML capabilities

AI & ML Development Capabilities

AI rarely works in isolation. We connect it with your software, data, cloud platforms and business systems so it can actually be used day to day.

Generative AI & LLMs

Help people find answers, work with documents and interact naturally with business knowledge.

AI assistants and copilotsRetrieval-Augmented GenerationEnterprise knowledge searchConversational AIDocument intelligence

AI Agents

Give AI the ability to do more than respond. Agents can use tools, interact with systems and complete multi-step work.

AI agent developmentAgentic workflowsMulti-agent systemsTool and API integrationHuman-in-the-loop workflows

Machine Learning

Use your data to spot patterns, predict outcomes and support better business decisions.

Predictive analyticsForecastingRecommendation systemsFraud and anomaly detectionRisk and credit modelling

Computer Vision

Turn images, video and documents into usable information, alerts and automated actions.

Object detectionImage recognitionVisual inspectionOCR and document understandingVideo analytics

AI Engineering & MLOps

Take promising AI experiments and turn them into systems people can rely on in production.

MLOps and LLMOpsModel deployment and observabilityAI infrastructureModel evaluationAI governance and security

Intelligent Automation

Reduce repetitive work by combining AI, business rules and workflow automation around the way your teams already operate.

AI-powered workflow automationIntelligent document processingERP and CRM automationDecision automationHuman and AI workflows

AI across industries

Where Can AI Create Value in Your Business?

The real question is not ‘Where can we use AI?’ It is ‘What business problem is worth solving with it?’ Explore practical AI-powered solutions across the industries DigiWagon works with.

01 / 09Credit & risk intelligence · Fraud & anomaly detection

FinTech

Apply AI across lending, risk, fraud and customer operations.

Credit & risk intelligenceFraud & anomaly detectionLending automationFinancial AI assistants
Explore FinTech

Our work

AI & Machine Learning in practice.

Engagements where this is what we actually built. 4 of them are written up in full.

View all case studies
The AI-powered AML screening platform on a tablet, showing a screening queue with match statuses and risk flags.FinTech

AI-Powered AML Screening Platform: Modernising Financial Crime Compliance

Consolidated AML screening, automation, and case management into a single AI-powered platform, enabling faster onboarding, reduced false positives, and real-time compliance visibility for financial institutions.

70%Faster information retrieval60%Reduction in manual knowledge discovery effort
The TractorIQ predictive maintenance dashboard on a laptop, showing engine speed, oil temperature and coolant dials.Manufacturing

Smart Predictive Maintenance for Tractors: Bringing AI to the Service Bay

An AI-powered predictive maintenance solution that predicts equipment health, optimizes maintenance schedules, and brings legacy tractors into a unified intelligent monitoring platform.

45%Faster component issue detection35%Reduction in unplanned downtime risk
The AIVA data assistant open on a laptop, showing search results beside New Search, Search History, Upload Data and All Uploads actions.Manufacturing

Building an AI Data Assistant for a Global CPG Leader

DigiWagon built a production-grade RAG platform for a global CPG leader, using Azure AI to help R&D and compliance teams quickly search, synthesise, and generate insights from millions of scattered documents.

70%Faster information retrieval60%Reduction in manual knowledge discovery
Production intelligence flow linking active sites, equipment, risk alerts and operational insights to smarter decisions.Manufacturing

Mining Intelligence: Automating Insights Below the Surface

An AI/ML-enabled prediction engine connecting plant data to automated forecasts, reducing human error, speeding up decisions, and scaling seamlessly across plants.

45%Faster insight discovery35%Reduction in manual analysis effort

Technology

Technologies Behind Our AI & ML Systems

We choose the models, platforms and engineering tools around the product, the data, the operating environment and the level of control the system needs.

AI & Machine Learning

  • OpenAI
  • Azure OpenAI
  • PyTorch
  • TensorFlow

AI Engineering

  • LangChain
  • LangGraph
  • Retrieval-Augmented Generation
  • Vector search
  • Model evaluation frameworks

Data & Search

  • PostgreSQL
  • MongoDB
  • Elasticsearch
  • Vector databases
  • Modern data platforms

Cloud & Infrastructure

  • Microsoft Azure
  • AWS
  • Docker
  • Kubernetes
  • Cloud-native APIs

How we work

From AI Opportunity to Production

A good AI project starts with a problem worth solving. Everything after that is about proving it works and engineering it properly.

01

Discover the Opportunity

Identify where AI can create measurable value, understand the available data and define the right business outcome.

Focus
ProblemValueDataFeasibility
02

Prove the Value

Test the idea through focused prototypes, experiments and measurable success criteria before committing to full-scale implementation.

Focus
PrototypeValidationEvidence
03

Engineer for Production

Develop the AI, application, data pipelines, integrations and user experience as one production-ready system.

Focus
AISoftwareDataIntegration
04

Operationalize & Evolve

Deploy securely, monitor performance, govern AI behaviour and improve the solution as business needs evolve.

Focus
DeployObserveGovernImprove
Discover01 Discover the OpportunityProve02 Prove the ValueEngineer03 Engineer for ProductionEvolve04 Operationalize & Evolve

Why DigiWagon

Why DigiWagon for AI & ML Development?

AI succeeds when product, data, software and operational engineering are considered together.

AI + Software Engineering

We engineer the applications, workflows and integrations around the model—not just the model itself.

Data Foundations

Reliable AI starts with data that is usable, connected and engineered for the task.

Enterprise Integration

Connect AI with APIs, databases, ERPs, CRMs, cloud platforms and existing business systems.

Production-First Thinking

Security, evaluation, governance, observability and human oversight are considered before deployment, not added later.

Insights

Thinking Behind Production AI.

Practical perspectives on AI engineering, data foundations and building systems that last beyond the prototype.

Enterprise AI architecture blueprint: six production layers from data to governance, with a contract between each layer.
AI & Machine Learning

Enterprise AI Architecture: The Production Blueprint

· Akash Thakor · 10 min read

AI agent security for FinTech showing an AI agent protected by tool permissions, human approvals, sandboxing, monitoring, data boundaries, and audit controls.
AI & Machine Learning

AI Agent Security Guide for FinTech

· Jigar Vavadia · 6 min read

Feature image showing governed enterprise AI agents inside a decision-harness architecture with context compilation, dual-gate policy enforcement, decision traces, trust graduation, and audit-ready controls.
AI & Machine Learning

Governed Enterprise AI Agents: A Decision-Harness Architecture

· Kartik Gajjar · 10 min read

All AI & Machine Learning writing

FAQ

Frequently Asked Questions About AI & Machine Learning Services

Clear answers to common questions about applying and operating AI in real business systems.

01What AI and machine learning services does DigiWagon provide?

DigiWagon develops Generative AI applications, AI agents, machine learning models, computer vision systems, intelligent automation, and the AI engineering and MLOps needed to run them reliably in production.

02How can artificial intelligence help a business?

Artificial intelligence can help businesses automate repetitive work, improve decision-making, predict future outcomes, make enterprise knowledge easier to access and introduce intelligent capabilities into digital products and operations.

03What is the difference between Generative AI, AI Agents and Machine Learning?

Generative AI creates and understands content such as text, documents and conversations. AI agents can use tools and business systems to complete tasks. Machine learning learns from data to identify patterns, predict outcomes and support decisions.

04What are machine learning services?

Machine learning services typically include preparing data, developing and evaluating models, integrating predictions into applications, deploying models and monitoring them in production. DigiWagon approaches machine learning as part of a broader engineering system rather than treating the model as a standalone deliverable.

05What are artificial intelligence solutions?

Artificial intelligence solutions use technologies such as Generative AI, AI agents, machine learning and computer vision to improve products, automate workflows, interpret information or support decisions. The right solution depends on the business problem, available data and systems it needs to work with.

06How can AI be used in business?

AI can support businesses by automating repetitive work, improving access to knowledge, predicting outcomes, detecting anomalies, assisting employees and adding intelligent capabilities to digital products. The strongest use cases usually begin with a specific workflow, decision or customer problem.

Ready to Put AI to Work?

Whether you have a clear AI use case or are still figuring out where AI can help, we can help you identify the right starting point.

Discuss Your AI Initiative Start an AI Discovery

Ask an AI about this page

Before you choose a partner, ask your own AI

One click opens the assistant you already use with a question that points it at this page, so the answer comes from what we publish, not a guess.

The question it opens withRead https://digiwagon.com/artificial-intelligence-machine-learning-service and explain how DigiWagon runs a AI & ML Development engagement, what I should expect in the first 90 days, and how to judge whether a partner like this fits a team of our size. Stick to what the page says and mark anything you are not sure about.

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