Olakai Use Cases
Agentic automation is outpacing measurement.
AI Agents and GenAI tools now drive work across enterprise systems, yet most leaders lack visibility into where automation happens, how it performs, or what ROI it delivers. Olakai provides intelligence first – measuring agentic and human workflows alike, then layers in governance and enablement so enterprises scale AI with evidence, control, and speed.
Intelligence as the Engine of Productivity
Olakai turns raw AI usage into measurable efficiency and productivity gains. Each interaction across Agents, GenAI tools, and SaaS systems is captured, benchmarked, and translated into insights leaders can act on. Every use case shows how enterprises make AI, and the Agents that power it – accountable, measurable, and scalable.
Agent ROI & Efficiency Optimization
Boards demand ROI. Finance leaders want agentic workflows and AI investments tied to measurable business outcomes, not pilots and spend. Without quantification, automation looks like hype instead of value.
What Olakai Does
- Tracks efficiency gains, time saved, and cost savings per agentic workflow, bottom-up and verifiable
- Benchmarks performance by persona, department, and enterprise, with trend visibility
- Delivers board-grade reporting and ROI insights for CIOs and CFOs
Benefits
- Board-ready proof of agentic and AI-driven business impact
- Optimized cost structures with clear reinvestment levers.
- Strategic allocation of AI resources to the highest-yield areas.
Risk of Inaction
Budgets shrink, adoption slows, and AI investment loses executive support.
AI Usage Intelligence & Insights
Blind spots kill AI programs. Most enterprises lack visibility into how Agents, GenAI tools, and SaaS systems actually work together. Leaders need to see not just adoption levels, but workflow quality, risk exposure, and business impact in real time
What Olakai Does
- Monitors and classifies every Agentic workflow, prompt, and interaction across systems
- Detects sensitive data exposure or policy violations instantly, with contextual awareness
- Segments insights by Agent, persona, department, region, and more
- Surfaces adoption gaps, efficiency lift, and performance trends in live dashboards
Benefits
- Early detection of risks without slowing innovation
- Continuous visibility into every Agent and AI workflow across the enterprise
- Actionable intelligence leaders can trust, not static reports
Risk of Inaction
Agentic workflows operate unchecked, Shadow AI expands, and governance fails to keep pace.
Measurement & OLA Index™
The foundation of enterprise AI is intelligence. Leaders need to see where agentic workflows are operating, where automation delivers measurable gains, and how to prove ROI in hours and dollars. Without visibility, strategy is guesswork and AI remains unproven.
What Olakai Does
- Benchmarks agentic, human, and SaaS-AI adoption daily with the OLA Index™
- Quantifies time saved and net value created across automated workflows
- Maps and measures AI maturity by AI Agent, team, region, and application
- Produces board-ready dashboards on efficiency, automation, and ROI
Benefits
- Real-time evidence of AI and Agent performance across the enterprise
- Proof of ROI that boards, finance, and AI task forces can trust
- Data-driven strategy to scale adoption and direct investment
Risk of inaction
Agents operate in the dark, AI remains a cost center, and executive confidence erodes.
Agent Governance & Shadow AI
Adoption without governance is risk. Agentic workflows now span GenAI tools and SaaS systems – yet unapproved Agents, unmanaged prompts, and hidden integrations create Shadow AI. Enterprises need visibility and control to turn this complexity into safe, governed automation.
What Olakai Does
- Acts as a semantic firewall across Agents, LLMs, and SaaS environments
- Uses SDK and API integrations to detect, log, and classify all AI and Agent activity
- Enforces compliant adoption through adaptive, role-based policies
- Applies AI Semantic Filters™ to monitor and remediate risky workflows in real time
Benefits
- Unified visibility across all agentic and AI usage
- Continuous enforcement of enterprise policies without disrupting productivity
- Audit-ready transparency for compliance, risk, and board reporting
Risk of Inaction
Shadow AI expands, Agent behavior goes unchecked, and governance collapses.