Opportunity unclear
Find the opportunity worth funding
Sort promising ideas from expensive distractions before teams commit budget, attention, or political capital.
Explore the AI Opportunity & Value SprintAI value creation and implementation partner
Turn AI into measurable operating value.
H2H helps mid-market and enterprise organizations identify where AI can improve important work, redesign the workflow, implement the right AI or automation, build in the controls it needs, and measure whether it worked.
AI operating map
Make the path visible before the work gets expensive.
H2H turns AI conversations into a sequence leaders can inspect: decide what matters, redesign the work, govern consequential moments, then scale only when the evidence supports it.
01
Decide
Choose the business or operating question before selecting a model, vendor, or build path.
Output: A named opportunity, owner, assumptions, and next investment choice.
02
Redesign
Map the people, systems, data, reviews, exceptions, and handoffs that make the workflow real.
Output: A future-state operating path with the least complex credible intervention.
03
Govern
Define what AI may see, suggest, decide, and do where sensitive data or consequential actions appear.
Output: Policy, approval, trace, and exception boundaries where the workflow needs them.
04
Scale
Compare observed operation with the agreed evidence plan before expanding the motion.
Output: A choice to expand, revise, close a gap, choose another path, or stop.
What brings you here?
Start with the decision you need to make.
You do not need to enter through the same engagement. Choose the path that matches what is already clear.
Need already defined
Change a workflow outcome
Fix a workflow that is too slow, too manual, too risky, or too hard to scale by redesigning the work and the supporting technology together.
Explore workflow transformationNeed already defined
Build a new AI product or capability
Define the user job, the product boundary, the AI behavior, and the review path before the first governed release gets built.
Explore AI-native product developmentNeed already defined
Control production AI
Put policy, approvals, visibility, and traceability around AI users or agents before they touch sensitive data or consequential tools.
Explore AI governance and securityObservable outcomes
Measure the work, not the AI activity.
H2H establishes the current state and target before choosing a technology path. The model below shows the measurement categories a pilot should make visible; it is not a promised result.
Baseline
What the customer confirms is happening now: effort, time, quality, risk, or capacity.
Target
What the pilot is intended to change, including quality, control, and adoption constraints.
Observed evidence
What the team actually sees during the pilot, used to decide whether to expand, revise, or stop.
Categories only. No financial value, ROI, or risk-reduction percentage is calculated here.
H2H and Tutela
Services implement the workflow. Tutela governs the risky moment.
H2H helps you figure out what AI should change, build the working path, and prove what the pilot produced. Tutela by H2H is used when the workflow needs runtime policy, approvals, data or agent boundaries, visibility, or customer-managed control.
H2H services lane
We help you figure out exactly what AI your customer needs, build the working path, and show what the pilot produced.
workflow requires controls
Tutela product lane
Tutela sits at the risky moment: when an AI user or agent touches sensitive data, asks for approval, or tries to act.
Concrete example
Picture the work in a support workflow.
This is an illustrative composite example, not customer work or a promised result. It shows the kind of practical artifact a buyer can discuss internally after a first H2H engagement.
Request enters
Email, chat, forms, and case systems create one visible intake path.
Context gathered
Approved sources, account facts, prior activity, and rules are assembled.
AI assists
The assistant classifies, summarizes, drafts, or recommends within its lane.
Human approves
Operators keep authority over sensitive commitments, exceptions, and escalations.
Action logged
System writes, handoffs, approvals, and exceptions leave a usable trail.
Evidence reviewed
Baseline, target, observed operation, quality, and trace completeness are compared.
Current pain
Support work is split across email, chat, knowledge systems, and case tools.
Search work
Handoffs
Escalations
H2H intervention
Redesign intake, context gathering, AI-assisted drafting, approval, routing, and feedback as one workflow.
Workflow map
Review model
Integration path
Evidence produced
Compare the agreed baseline with observed operation, quality, exceptions, and trace completeness.
Baseline
Observed evidence
Trace fields