AI Consulting & Integration

What We Do

AI consulting is not about recommending AI for its own sake. It is about understanding your business clearly enough to know where AI creates genuine value, where it does not, and what a realistic path to that value looks like given your data, systems, and current capabilities.

We cover the full advisory lifecycle from initial AI audits and opportunity identification through to roadmap design, vendor evaluation, architecture, and hands-on integration into your existing systems. We are technology-agnostic and commercially independent. Our recommendations are based on what is right for your business, not on what we prefer to build.

Our AI Consulting & Integration Services

AI Opportunity Assessment & Feasibility Analysis

A structured assessment of your operations, data landscape, and technology environment identifying where AI creates genuine value and what is realistically achievable given your current constraints.

High-value AI use case identification across business functions

Data readiness assessment quality, volume, structure, accessibility

Technical feasibility evaluation per use case

Honest risk assessment including where AI is not the right tool

Preliminary ROI modelling and business case development

AI Strategy & Roadmap Development

A sequenced, realistic implementation plan specific enough to act on, prioritised to deliver early value, and grounded in your actual data maturity, budget, and team capability.

AI vision and objectives aligned to your business goals

Phased roadmap with clear milestones and investment planning

Build, buy, and partner decisions for each initiative

Organisational capability assessment and skill gap identification

Governance framework for responsible AI deployment

AI Audit & Maturity Assessment

A structured review of existing AI initiatives surfacing model drift, brittle integrations, data pipeline gaps, and governance issues that internal teams often cannot see clearly from inside.

Review of existing AI models, systems, and data pipelines

Performance benchmarking against original objectives

Model drift and data quality assessment

Compliance and responsible AI governance review

Prioritised remediation plan with clear recommendations

AI Architecture Design

Technical architecture designed before development begins defining data flows, model components, integration points, infrastructure, and monitoring. Good architecture decisions made early prevent expensive rework later.

End-to-end AI system architecture design

Model serving and inference architecture for production workloads

Cloud infrastructure design AWS, Google Cloud, Azure

MLOps architecture for model versioning, monitoring, and retraining

Security and data governance architecture

AI Vendor & Tool Evaluation

Structured, technically rigorous vendor evaluations with proof-of-concept testing, commercial terms review, and lock-in risk assessment. We are not aligned with any vendor and receive no referral fees.

Requirements definition and evaluation criteria development

Structured evaluation across AI platforms and LLM providers

Proof-of-concept design and execution for shortlisted options

Long-term viability and lock-in risk assessment

AI Integration into Existing Systems

We handle the full integration not just the model. Data pipeline engineering, API design, latency management, error handling, and UI changes, ensuring AI capability reaches the users and workflows it is meant to serve.

AI model integration into web and mobile applications via APIs

CRM, ERP, and helpdesk system integration

Workflow automation connecting AI outputs to downstream processes

Testing, validation, and performance benchmarking

AIOps & MLOps Setup

The operational infrastructure that makes AI systems maintainable at scale model versioning, automated retraining, drift detection, alerting, and the processes your team needs to manage AI responsibly in production.

Model versioning with MLflow and DVC

Automated retraining pipelines with Apache Airflow

Drift detection and alerting with Evidently AI and Prometheus

Governance documentation and audit trail setup

Responsible AI & Governance Consulting

We help organisations build AI with fairness, explainability, and compliance as engineering requirements covering India’s DPDP Act, GDPR, RBI and SEBI guidelines, and healthcare regulations.

AI bias assessment and fairness evaluation

Explainability framework for high-stakes AI decisions

Data privacy impact assessment for training and inference

AI governance framework and responsible AI policy development

AI Change Management & Organisational Enablement

AI projects fail for organisational reasons as often as technical ones. We manage the human side communication, team training, workflow redesign, and building the internal capability to sustain AI beyond the initial engagement.

AI literacy programmes for leadership and operational teams

Change communication planning for AI adoption

Internal AI champion and centre of excellence development

Core Consulting Capabilities

AI Opportunity Identification & Prioritisation

A structured methodology based on data availability, process characteristics, decision complexity, and cost of errors prioritised by business impact and implementation feasibility.

Data Strategy & Architecture

AI capability is constrained by data quality more than model sophistication. We assess your data landscape and design the foundation your AI programme needs.

Enterprise AI Architecture

Shared data infrastructure, common model serving platforms, standardised MLOps, and governance across multiple teams and use cases.

LLM & Generative AI Strategy

Identifying where LLMs create genuine value, designing RAG and fine-tuning architectures, managing cost at scale, and addressing hallucination, bias, and security risks.

AI Integration Architecture

Connecting AI to legacy systems via APIs, event-driven patterns, and data pipeline engineering without requiring the rest of the system to be rebuilt.

AI Risk & Compliance Assessment

Model bias, privacy implications, regulatory gaps, and reputational risk with mitigation strategies appropriate to the risk level of each use case.

Technology Platforms We Work With

We are platform-agnostic. Our assessments cover the full landscape we are not aligned to any vendor.

MLOps & Model Lifecycle

MLflow • DVC • Weights & Biases • Evidently AI • Seldon Core • BentoML

LLM Orchestration & RAG

LangChain • LlamaIndex • Haystack • Semantic Kernel

Cloud AI Platforms

AWS (SageMaker, Bedrock, Lambda) • Google Cloud Vertex AI • Azure ML & OpenAI Service • Databricks • Snowflake

LLM & GenAI Platforms

OpenAI GPT-4 • Anthropic Claude • Google Gemini • Meta LLaMA 3 • Mistral • Cohere

Data Engineering

Apache Airflow • Kafka • Spark • dbt • Fivetran

Enterprise Integration

REST APIs • GraphQL • Webhooks • MuleSoft • AWS Step Functions

CRM & Enterprise Systems

Salesforce • Zoho • SAP • Microsoft Dynamics • HubSpot • Freshdesk • ServiceNow

Industries We Serve

Healthcare

AI roadmap for hospitals and diagnostic labs, data strategy for clinical AI, responsible AI framework, and compliance consulting under India's health data regulations.

Finance & Banking

AI strategy for banks and NBFCs, feasibility assessment for fraud detection and credit scoring AI, RBI and SEBI compliance review, and GIFT City regulatory consulting.

Retail & E-commerce

AI opportunity assessment for personalisation, demand forecasting, and support automation with vendor evaluation and integration into existing commerce platforms.

Manufacturing

AI maturity assessment, feasibility analysis for predictive maintenance and quality control, integration consulting for MES and ERP environments.

Logistics & Supply Chain

AI roadmap for logistics optimisation, data strategy for forecasting and route optimisation, and integration consulting for TMS and WMS systems.

Education

AI strategy for EdTech platforms, data privacy consulting for student data, and integration of AI tutoring and admin automation tools into existing LMS platforms.

How We Work

We assess your business context, data landscape, and AI opportunities worth pursuing including being honest where the data doesn’t support a particular application.

A phased implementation plan with clear milestones, build-buy-partner decisions, and investment estimates specific enough to act on.

Technical architecture and vendor evaluations with rigorous proof-of-concept testing against your actual requirements.

We remain actively engaged through build whether through our own team, alongside your engineers, or with existing vendors.

Post-deployment performance review, model update advisory, and ongoing consulting support as your AI programme scales.

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Why Web Chip Armor

Commercially independent no vendor alignment

We are not aligned to any AI platform, cloud provider, or tool vendor. Our recommendations are based solely on what is right for your business. No referral fees, no preferred vendors.

Implementation experience informs the consulting

We have built AI systems in production. We know where implementations go wrong, what architecture decisions create problems at scale, and the gap between a clean roadmap and a delivered system.

We stay through implementation, not just strategy

We don't hand over a strategy document and disappear. We work with you through architecture, integration, deployment, and ongoing operations.

Deep technical depth across the AI stack

Machine learning, NLP, LLMs, data engineering, MLOps, and enterprise integration genuine technical depth that allows us to review vendor claims, evaluate architecture, and engage credibly with your engineers.

Sector-specific experience

Healthcare, Finance, Retail, Manufacturing, Logistics, Education we bring relevant sector experience to every engagement rather than a generic consulting framework.

NDA before any project discussion

Your business strategy, data, and all project information remain strictly confidential throughout and after the engagement.

Frequently Asked Questions

What is the difference between AI consulting and AI development?

AI consulting covers the advisory work identifying use cases, designing strategy and roadmap, selecting tools and vendors, designing architecture, and managing organisational change. AI development is the engineering work of building and deploying AI systems. We offer both, which means our consulting advice is grounded in implementation reality, and we can carry recommendations through to delivery.

How long does an AI consulting engagement take?

An AI opportunity assessment and roadmap typically takes four to eight weeks. A comprehensive AI audit takes two to four weeks. Architecture design and vendor evaluation for a specific initiative takes three to six weeks. Ongoing advisory retainers run monthly or quarterly.

What deliverables do we receive?

Typically: a prioritised AI opportunity assessment, a phased implementation roadmap with investment estimates, architecture documentation, vendor evaluation reports, and a governance and risk framework all written for a business audience, not a technical one.

We already have AI systems deployed can you audit them?

Yes. We assess current model performance against business objectives, identify drift and data quality issues, review integration architecture for brittleness, and evaluate governance against current regulatory requirements. The output is a prioritised remediation plan with clear recommendations.

How do you handle regulatory compliance DPDP Act, RBI, SEBI?

We assess your AI programme’s compliance with India’s DPDP Act, RBI digital lending and operational risk guidelines, SEBI regulations for investment platforms, and sector-specific healthcare data requirements. Compliance architecture is designed in from the start, not retrofitted.

Do you work with businesses at the very beginning of their AI journey?

Yes. Many of our engagements begin with organisations that have identified AI as strategically important but have not yet started. We help them avoid the common early mistakes investing before data infrastructure is ready, starting with technically interesting but low-value use cases, and underestimating the organisational change required.

Let's Build Your AI Strategy

Whether you’re at the start of your AI journey, trying to get more value from an existing investment, or navigating a specific decision we’d like to hear about it. We’ll give you a straight answer on how we can help, what the right scope is, and what it would cost.