Your company already has the data. Nobody can find it in time.
Knowledge is scattered across drives, wikis, mailboxes and departments. Employees ask colleagues instead of searching, contract review is a bottleneck, reporting is assembled manually, and staff use public AI tools with confidential data because no approved option exists.
Create a permission-aware assistant over approved internal knowledge and support reporting, contract review and routine handoffs. Agree source ownership, access, logging and escalation across departments before a wider rollout.
Corporates, groups and companies with 100+ employees.
Start with one workflow, measure it against the current baseline and expand only after the result is visible.
Reduce search and coordination friction without weakening enterprise access controls or accountability.
Open each stage to see the problem, action, deliverable and KPI behind the workflow.
Enterprise AI initiatives start in separate departments without one portfolio, business case or shared definition of success. Pilots multiply while strategic priorities, ROI and risk remain unclear.
Map the highest-value opportunities across departments, score impact, feasibility, risk and readiness, and turn the priorities into an executive roadmap with accountable owners and measurable outcomes.
AI opportunity portfolio, prioritization model, executive roadmap, business cases, owners and an AI governance decision log.
See approvals, knowledge, reporting and cross-department handoffs as one operating system instead of isolated automation ideas.
Map the highest-value opportunities across departments, score impact, feasibility, risk and readiness, and turn the priorities into an executive roadmap with accountable owners and measurable outcomes.
Define the AI operating model, decision rights, centre-of-excellence or federated roles, escalation paths and the workflows that connect AI systems to business teams.
Create a data and knowledge inventory, connect approved sources, apply access and retention rules, and deploy grounded assistants with citations, monitoring and human review where the decision matters.
Connect finance, operations and outcome data in executive dashboards, define KPI ownership, track benefits against the business case and explain the drivers behind performance changes.
Classify use cases by risk, maintain a control and model register, monitor data handling and outputs, document approvals, and route sensitive decisions through the right human and compliance review.
Build a change plan around real employee journeys, train teams by role, create champions and feedback loops, publish practical safe-use guidance and measure adoption and confidence over time.
Deliver concise decision briefs with evidence, scenarios, risks and recommended actions. Review the portfolio regularly, capture lessons, stop low-value work and expand proven capabilities through a repeatable improvement cycle.
Bring cycle time, exceptions and ownership into one recurring cross-functional review so leadership can see where the process still breaks.
Start with one department, a bounded set of approved sources and a defined group of users. Prove answer quality, permissions and adoption before adding reporting or cross-department workflows.
For enterprise work, these are the operating boundaries HAY AI can support today.
Client-approved cloud or API environments and private deployment patterns where the chosen architecture supports them. We can connect to existing identity, document and business systems rather than require a separate public tool.
Only approved sources and tools are connected. Access can follow existing role and identity permissions, and high-impact actions stay behind explicit approval.
Where the application or data store is under our control, we can configure the retention and deletion controls that system supports. Third-party provider retention limits are reviewed before use.
HAY AI does not claim ownership of your source data. For custom builds, project code, configurations, prompts, evaluation assets and documentation can be handed over; third-party and model-provider terms still apply.
Documented handover and knowledge transfer are supported. HAY AI can also stay involved for monitoring, updates and improvement work after launch.
Your team keeps ownership of business rules, data permissions and source systems. With ongoing support, HAY AI maintains only the application or integration items we operate; after handover, day-to-day operation moves to your team.
Choose one shared-service or cross-department workflow and one measurable target first. Expand only after owners accept the operating change and the evidence is visible.
Permissions, source citations and owner approval are built in.
Connect the collaboration, ERP, CRM, ticketing and document tools already used by the teams instead of forcing a new enterprise stack.
Review the agreed measures: Search time, answer quality, adoption and avoided repetitive requests. Use these to assess business outcomes and decide the next step.
Suggested start: one workflow can go live first; the next measurable improvement is added only after the first review.
Book a free 30-minute discovery call. We will identify which use case is worth testing first and what evidence should decide the next step.
Send us the workflow, problem or idea you want to discuss. We’ll reply within one business day.
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