Make your coreworkflowsperform betterwith AI.

Enterprise AI transformation

Agentic Native Integration (ANI) helps organizations put AI to work across their business. We redesign workflows, connect shared knowledge, and train teams to reduce manual work and improve results.

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Workflow improvement

How ANI transforms the way your teams work.

We redesign the steps, systems, and responsibilities that connect your team’s work.

Current state
After ANI

Workflow

Current state

AI helps with individual tasks. People still connect the steps.

Teams copy information between systems, repeat instructions, and wait for someone else to move work forward.

After ANI

Each step has an owner and a clear handoff.

We define what AI handles, what people review, and how information moves between your systems.

Less manual coordination. Faster completion.

Shared knowledge

Current state

Teams repeat work they could reuse.

Useful prompts, source material, and decisions stay in separate chats and folders.

After ANI

Shared knowledge that teams and agents can reuse.

Organize approved source material, reusable instructions, and decisions in one maintained place, with an owner responsible for keeping them up to date.

Look for Less duplicate work and fewer conflicting outputs.

Team capability

Current state

AI use depends on a few experienced people.

Colleagues have access but need help applying AI to their work.

After ANI

Teams can run and improve AI workflows independently.

We train people on their own work, including how to review outputs and when to ask for help.

Look for More people meeting quality standards without expert help.

AI spending

Current state

AI costs are scattered across tools and teams.

Leaders cannot see which workflows account for spending or where licenses go unused.

After ANI

Workflow owners can account for AI costs.

We bring tool costs, reported token usage, and human review effort into a recurring workflow-level review, with budgets and assigned owners.

Track Spend by workflow, unused licenses, and cost per completed output.

Business results

Current state

AI usage is visible. Its business impact is harder to establish.

Usage reports show activity, but may not show improvements in completion time, quality, or cost to complete the work.

After ANI

Leaders can compare results against a baseline.

We establish the starting point and track an agreed business measure, alongside quality and rework, to decide what to improve, expand, or stop.

Track Business results against the baseline; time freed and cash savings reported separately.

These are target changes, agreed with your team at the start. Cost visibility depends on your tools’ reporting; implementation and human review also require team time.

AI performance & governance

How we assess and improve AI use.

We assess each priority business unit against the same criteria, so leaders can compare results and decide where to invest.

Adoption
Check use of approved AI tools and identify gaps in access or support.
Team capability
Assess practical skills and provide training to close the gaps.
Workflow results
Measure completion time, output quality, and rework.
Evaluations
Test AI against agreed standards using real work examples. Repeat the tests when the system changes.
Feedback loops
Use errors, corrections, and employee feedback to improve workflows. Check whether quality improves or completion time falls.
Cost & capacity
Compare AI costs and review effort with workflow results. Finance validates cash savings; we report time freed separately.
Governance
Assign accountable owners and define when human approval is required. Review these controls as workflows change.
Founder-led delivery

Work directly
with Christina.

Christina Kurbanov brings a decade of experience across strategy, operations, and organizational transformation, including AI transformation, integration, and training at Fortune 100 companies. Work directly with Christina and your leadership team, from the first assessment to full integration.

Career background: Meta, Instagram, Nike and Lululemon.

Christina's background ↗

Where should AI
work better?

Tell us where manual work is slowing your team down. We’ll discuss what AI could take on and where to start.

Talk to Christina ↗

christina@ani-enterprise.com