IT M&A

IT Due Diligence Scope

Software assessment for Product based companies (Software build, architecture, infrastructure, software security, customer support & software dev team, product & software dev roadmap)
3rd party or inhouse developed apps for front end operations
ERP, Finance, HR, CRM & other back-of-house systems
Infrastructure - data centre (inhouse or 3rd party), cloud infra (Azure, AWS, GCP, OCI, others)
IT Service management - internal IT supported inhouse or by 3rd party vendors
Cyber Security set up - cyber tools, vulnerability assessment, pen test, cyber audits, cyber insurance
IT Capex/Opex - comparison benchmarks & trends
IT Project roadmap - assessment of investment needed to bring IT to sufficient maturity
Digital Marketing capabilities - maturity of digital tools, Google Analytics, SEOs, Paid digital advertisements
IT Org - comparison against benchmarks, assessment if team or leadership has sufficient maturity, assessment of 3rd party IT vendors

AI Strategy: assess how AI supports the business and creates value. Is AI actually helping generate revenue, keep customers, or reduce costs?
Data Governance: assess if data is used safely, properly, and without bias, analysis of how data is implemented and where the training data comes from
Model Development: assess how AI models are built and trained, is AI just a basic layer built on top of someone else’s API, or does the company understand every AI model being used with clear documentations, AI framework being used; LLM, RAG, Agentic AI, AI Agents
Model Monitoring (Model Training, Evaluation & Testing): assess how the AI is trained and tested, and how its performance is measured (like accuracy, testing methods, latency, etc.)
MLOps maturity assessment: asses if the models can be updated automatically, fix issues quickly, and monitor for unusual behaviour, assess how do they manage deployment, automation, and smooth running of AI systems
Security: assess how the company protect AI systems and data from risks and attacks, do they follow rules, check risks in LLMs, and make sure data and models are properly owned and licensed
Explainability & Compliance: Makes AI decisions understandable and ensures rules are followed
Team Capability: checks if the right people and skills are in place to manage AI, assesses role coverage (data engineers, ML engineers, MLOps, annotation), documentation culture, and key-person dependencies

IT Separation Management supports the seller to execute IT divestiture across IT domains.
We align with Separation Management Office (SMO) to complete IT separation within compressed timeframes & with limited resources
Typical IT Separation process involves
- Carve-out IT due diligence, building Carve-out IT blueprint, setting up and managing IT TSAs, Identifying one off separation and running cost for the NewCo, setting up IT Op Model
- Selection of various vendors supporting IT Separation of Applications, Infrastructure, Network & IT Service Management
- Migration of various IT Apps, Infrastructure & Data as part of IT Separation

Traversing through technology related challenges in a post merger integration may be challenging.
IT integration activities need to be initiated soon as part of Integration Management Office (IMO) along with other key work streams
Typical IT Integration process involves
- IT due diligence of the acquired entity, building IT Integration blueprint keeping IT ecosystem of the acquiring entity in consideration, building up IT Projects with understanding of the dependencies across IT sub-functions and cross-functional workstreams, , Identifying one off integration and running cost for the NewCo
- Selection of various vendors supporting IT Integration of Applications, Infrastructure, Network & IT Service Management
- Migration of Various IT Apps, Infrastructure & Data as part of IT Integration