Industries
Olakai for Technology & Software
Measure AI ROI, govern risk, and prove value across your SaaS organization.
Your AI Is Delivering Results. Now Prove It to the Board.
Technology companies were the first to adopt AI at scale. Over 90% of tech organizations report regular AI use, and engineering teams are seeing 10-20% cost reductions from code assistants, automated testing, and root-cause analysis. The tools work. The adoption isn’t the problem.
The problem is proving it. Only 6% of organizations have achieved true AI maturity where gains compound across the business. Meanwhile, every team deploys its own AI tools — Copilot in engineering, AI scoring in sales, chatbots in customer success — each in its own silo with its own dashboard, none connecting back to business KPIs like ARR retention, pipeline velocity, or customer lifetime value. SOC 2 and ISO 27001 audits now expect documentation of how AI tools access customer data, and shadow AI proliferates without centralized governance. Without a measurement layer across all of it, AI pilots that show promise never scale because no one can prove their value to finance.
By the Numbers
90%+ of tech companies use AI regularly, but only 6% have reached true AI maturity.
The gap between adoption and maturity is a measurement problem — you can’t scale what you can’t prove.
Example KPIs for Common Agentic AI Workflows
Technology companies deploy AI across customer success, sales, support, marketing, and legal. Olakai gives you the KPIs to prove each workflow is working, meeting compliance requirements, and delivering measurable value.
Example 1: Churn Risk Detection · Customer Success
Customer churn often becomes visible only after cancellation notices arrive, when it’s too late to intervene. This workflow continuously monitors product usage and engagement metrics, identifies declining patterns that predict churn risk, scores each customer’s risk level, and alerts CSMs with prioritized intervention tactics. For SaaS companies where a single enterprise account represents six or seven figures in ARR, catching churn signals weeks earlier transforms retention economics.
Key KPIs to measure with Olakai
Net Revenue Retention ARR retained from existing customers, including expansions.
Saved ARR per Quarter Dollar value of accounts retained after AI-triggered interventions.
Time to Intervention Days from churn signal detection to CSM outreach.
Example 2: Lead Qualification · Sales
Marketing generates thousands of leads monthly, but sales teams waste time sifting through unqualified prospects instead of engaging high-intent buyers. This workflow scores leads based on firmographic fit and engagement signals, routes qualified leads to the appropriate sales rep, and sends personalized follow-up within minutes. The result is a pipeline that moves faster because reps spend time on prospects who are ready to buy.
Key KPIs to measure with Olakai
MQL-to-SQL Conversion Percentage of marketing-qualified leads that become sales-qualified.
Lead Response Time Minutes from lead creation to first sales contact.
Pipeline Velocity Speed at which qualified deals move through sales stages.
Example 3: Help Desk Ticket Routing · IT
Help desk teams are overwhelmed with tickets that sit in general queues for hours before reaching the right specialist. This workflow analyzes incoming requests using NLP, categorizes by issue type, determines priority based on keywords and user role, and routes each ticket to the most appropriate team. Routing accuracy jumps from roughly 60% with manual triage to 85%+ with AI, cutting response times dramatically.
Key KPIs to measure with Olakai
Routing Accuracy Percentage of tickets routed to the correct team on first assignment.
Mean Time to Resolution Hours from ticket creation to resolution.
Employee Satisfaction Score Internal CSAT rating for help desk interactions.
Example 4: Campaign Optimization · Marketing
Campaign optimization is manual and slow, causing budget waste on underperforming channels while winning tactics go underfunded. This workflow monitors multi-channel campaign performance in real-time, calculates ROI by channel and creative variant, reallocates budget from underperformers to top performers, and A/B tests creative variations automatically. Marketing teams stop guessing and start operating on data.
Key KPIs to measure with Olakai
Cost per Acquisition Marketing spend per new customer acquired.
Channel-Level ROAS Return on ad spend by channel and creative variant.
Time to Optimization Hours from campaign launch to first AI-driven budget reallocation.
Example 5: Contract Review · Legal
Reviewing SaaS agreements, vendor contracts, and licensing terms is meticulous and time-intensive, where missing a single unfavorable clause can expose the organization to significant liability. This workflow extracts key terms, flags non-standard or risky clauses against internal playbooks, and suggests specific redline changes. Legal teams review contracts in half the time while catching more issues than manual review alone.
Key KPIs to measure with Olakai
Review Cycle Time Days from contract received to fully reviewed.
Risky Clauses Identified Non-standard or risky clauses caught per review.
Contracts per Attorney Monthly contract throughput per reviewer.
Why Measurement Changes Everything
From Churn Reaction to Revenue Protection
Instead of discovering churn after the fact, measure exactly how many accounts were saved, how much ARR was retained, and what each intervention costs versus what it protects. Turn retention from a hope into a provable revenue line.
From Pipeline Fog to Sales Precision
Track MQL-to-SQL conversion, lead response time, and pipeline velocity to prove that AI lead qualification is accelerating deals. When you can show the data, sales gets more investment instead of cuts.
From Support Bottleneck to Scalable Resolution
Measure routing accuracy, resolution time, and employee satisfaction to prove your help desk AI is solving real problems. Data-backed support improvements earn trust from engineering and executive teams alike.
From Shadow AI Risk to Controlled Adoption
Replace “block everything” with “measure and govern.” See which unsanctioned AI tools employees use, quantify the SOC 2 and GDPR risk, and bring high-value usage into the fold with proper oversight.
From Marketing Guesswork to Proven ROAS
Connect AI campaign optimization to actual acquisition costs and channel performance. When you can show exactly how much budget was saved and revenue generated, marketing becomes a profit center.
From Legal Bottleneck to Scalable Review
Measure contracts per attorney and risky clauses caught. Prove to the business that legal is scaling capacity without adding headcount, turning a cost center into a strategic advantage.