Inventh AI consulting services help leadership teams decide where AI will create value, assess whether data, systems and people are ready, and set up governance so AI is used safely. Engagements range from a fixed scope AI readiness assessment to a full strategy and roadmap, and the same team can build what the strategy calls for.
Our approach
Most AI pilots fail for business reasons, not technical ones.
Pilots stall when nobody agreed what success looks like, the data was not ready or the people who should use the result were never involved. We start with those questions and only then choose the technology.
Value before models
Every recommendation is tied to a measurable business outcome, with the cost to achieve it stated up front.
Honest about readiness
We tell you plainly when your data, processes or teams are not ready, and what it takes to get there.
Strategy that ships
Our consultants work alongside the engineers who build AI systems, so plans are realistic and deliverable.
Where AI creates value
AI opportunities, function by function
We assess AI use cases against the work each function actually does, then prioritize by value, feasibility and risk.
Finance
Invoice and document processing, anomaly detection in transactions and faster forecasting.
Fewer manual hours at month end and earlier warning on cash.
Sales and marketing
Lead scoring, proposal drafting, content assistance and customer insight from CRM data.
More time selling, better targeted campaigns.
Customer service
Assistants that answer routine questions from your own policies and hand complex cases to people.
Faster responses and lower cost to serve.
Operations and supply chain
Demand forecasting, predictive maintenance and exception handling in order flows.
Less stock tied up and fewer disruptions.
People and knowledge
Internal assistants that find answers across documents, procedures and systems.
Less time searching, faster onboarding.
Leadership
Decision support that summarizes performance and explains what changed and why.
Faster, better informed decisions.
What we deliver
Our AI consulting services
Delivered as focused engagements or as an ongoing advisory relationship alongside your leadership team.
AI Strategy and Roadmap
A clear view of where AI fits your business goals, with a prioritized portfolio of initiatives and a phased roadmap.
AI Readiness Assessment
A review of your data, systems, security, skills and processes, with the gaps that must close before AI can deliver.
Use Case Discovery and Business Cases
Workshops that identify, size and prioritize use cases, each with costs, benefits and success measures.
AI Governance and Responsible AI
Policies, risk assessment, controls and oversight aligned with recognized frameworks and applicable regulation.
Model, Vendor and Platform Selection
Independent comparison of AI models, platforms and vendors against your requirements, costs and risks.
Proof of Value and Scale Up
Short, measured pilots that prove value with real data, followed by a plan to take what works to production.
From advice to production
Consulting backed by an engineering team
Our AI consultants and engineers work as one practice. When the strategy is agreed, the same team can build, integrate and run the AI systems it calls for.
Generative AI applications
Assistants, copilots and content tools grounded in your own documents and data.
AI agents and automation
Agents that carry out defined tasks across your systems, with permissions and audit trails.
Machine learning and forecasting
Predictive models for demand, risk, churn and pricing, built on your operational data.
Data foundations
The pipelines, data platforms and governance that every reliable AI system depends on.
Our AI adoption framework
From ambition to AI at scale
A staged approach that delivers value early and builds the foundations each next step needs.
Assess
Map goals, data, systems, skills and risks, and establish where AI can create measurable value.
Prioritize
Build a use case portfolio ranked by value, feasibility and risk, with business cases for the top candidates.
Prove
Run short pilots with real data and users, measured against success criteria agreed in advance.
Scale and govern
Take proven use cases to production under a governance model that manages risk, cost and quality.
Governance aligned with the NIST AI Risk Management Framework, ISO/IEC 42001 and, where it applies, the EU AI Act.
See our AI and machine learning servicesDecision ready outputs
What your leadership team receives
Every AI engagement ends with documents your executives can use to decide, fund and govern.
AI readiness report
Data, systems, skills, security and process readiness, scored with clear gaps.
Use case portfolio
Prioritized opportunities with value, feasibility, risk and effort for each.
Business cases
Costs, benefits, payback and assumptions for the leading use cases.
AI roadmap
Phased initiatives, dependencies and milestones over the next twelve to twenty four months.
AI policy and governance model
Acceptable use, risk classification, approvals, monitoring and accountability.
Vendor and platform recommendation
An independent comparison with a clear recommendation and its rationale.
The rules are changing
AI regulation and standards we advise on
AI governance has moved from optional to expected. These are the frameworks and deadlines shaping enterprise AI programs.
Reviewed September 2026
Since February 2, 2025
EU AI Act: prohibitions and AI literacy
Prohibited AI practices and AI literacy obligations under the EU AI Act have applied since February 2, 2025.
Since August 2, 2025
EU AI Act: general purpose AI
Obligations for general purpose AI models and the Act's governance rules have applied since August 2, 2025.
December 2, 2027
EU AI Act: high risk systems
Following the AI Omnibus amendment, rules for high risk AI systems in listed areas apply from December 2, 2027.
Standard
ISO/IEC 42001
The international standard for AI management systems gives organizations a certifiable structure for governing AI across its lifecycle.
Framework
NIST AI Risk Management Framework
NIST's framework, with its Generative AI Profile (NIST AI 600-1), is a widely used reference for identifying and managing AI risk.
December 2025
An open standard for AI agents
The Model Context Protocol joined the Linux Foundation's Agentic AI Foundation, a common way to connect AI agents to business systems.
Choosing the right engagement
AI consulting, AI development or both
| Criteria | AI consulting | AI development | Consulting and development |
|---|---|---|---|
| Best when | You need to decide where and how to use AI | The use case and approach are already clear | You want one team accountable from strategy to production |
| Main outputs | Strategy, readiness, business cases, governance | Working AI systems in production | Roadmap, pilots and production systems |
| Typical duration | Weeks | Months | Phased over months |
| Who leads | Consultants with engineering input | Engineers with product ownership | One joint team |
How we work
A typical AI consulting engagement
Listen
Interviews with leadership and the teams closest to the work, plus a review of goals, data and systems.
Analyze
Readiness assessment, use case discovery and sizing, and a review of risks and constraints.
Recommend
Prioritized portfolio, business cases, governance model and roadmap, presented to leadership.
Enable
Pilots, vendor selection support, training and hand over to delivery, by our team or yours.
Responsible AI
How we help you govern AI
Clear accountability
Named owners for every AI system, with defined approval steps before anything reaches customers or staff.
Risk classification
Each use case assessed for data sensitivity, impact and regulatory exposure, with controls to match.
Human oversight
People review decisions that matter, and users can see, question and correct AI outputs.
Monitoring and review
Quality, cost, drift and incidents tracked after launch, with regular reviews by the governance group.
Platforms
Platforms and models we advise on
Independent advice across the major AI platforms, chosen for your requirements rather than a vendor relationship.
AI models
Cloud AI platforms
Data and analytics
Governance
How we operate
Principles behind our AI advice
Independent recommendations
We recommend the model, platform or vendor that fits your needs, and disclose any partnership that could influence advice.
Your data stays yours
Client data is handled under NDA, used only for the engagement and never used to train third party models.
Plain language
No hype and no jargon without explanation. Leaders get clear options, trade offs and costs.
Measured outcomes
Every recommendation comes with the measures that will show whether it worked.
Connected capabilities
From AI strategy to AI in production
AI and Machine Learning
Generative AI, agents and predictive models, built and run in production.
ExploreAdvanced Analytics and BI
Trusted dashboards, forecasts and AI ready data.
ExploreEnterprise Application Development
ERP integration, workflow automation and modernization.
ExploreIT Consulting
IT strategy, cloud, security and technology cost reviews.
ExploreApplication Development Consulting
Architecture, build or buy decisions and delivery assurance.
ExploreDedicated Development Teams
Architects and engineers who extend your team.
ExploreEngagement models
Ways to work with us
AI readiness assessment
A fixed scope assessment of data, systems, skills and risks, with a prioritized use case portfolio.
AI strategy and roadmap
A complete strategy with business cases, governance model and a phased roadmap for leadership approval.
Ongoing AI advisory
Regular advisory time for leadership on AI priorities, vendors, governance and progress.
FAQ
Frequently asked questions
What does an AI consultant do?
An AI consultant helps an organization decide where AI can create value, assesses whether its data, systems and people are ready, builds business cases and a roadmap, and sets up governance so AI is used safely and responsibly.
How is AI consulting different from AI development?
AI consulting decides what to do and why: strategy, use cases, readiness and governance. AI development builds and runs the systems. Inventh does both, so the same team can take a strategy into production.
What is an AI readiness assessment?
A structured review of your data quality, systems, security, skills and processes that shows which AI use cases are feasible now and what needs to change for the rest.
How long does an AI consulting engagement take?
A readiness assessment typically takes a few weeks. A full strategy and roadmap takes longer, depending on the number of functions and use cases in scope.
Do we need an AI governance policy?
Yes, once AI is used on business data or with customers. A governance policy sets acceptable use, approval steps, risk controls and accountability, and supports compliance with rules such as the EU AI Act where they apply.
Which AI models and platforms do you recommend?
It depends on your requirements for quality, cost, privacy and integration. We compare options such as OpenAI, Anthropic, Google and open source models on Azure, AWS or Google Cloud, and recommend what fits.
Is our data safe during an AI engagement?
Yes. Client data is covered by NDA, stays in your environment wherever possible and is never used to train third party models.
Can you build what the strategy recommends?
Yes. Our AI and machine learning practice builds, integrates and supports the systems, or we hand over to your team with clear requirements.
Find out where AI will pay off in your business
Book an AI readiness assessment. We will review your data, systems and opportunities, and come back with a prioritized portfolio and roadmap your leadership team can act on.