Zero-Cost AI Pilot Until ROI

Deploy an AI agent to handle initial customer inquiries, routing only complex cases to human agents. This directly reduces average handle time and operational costs.

• Real Example: A telecom company reduced call center volume by 35% in the pilot phase, saving over $2M annually in labor costs.
• The ROI Fix: Fees begin only after the system demonstrates a pre-agreed reduction in tier-1 support tickets or cost-per-contact.

Implement AI models that analyze sensor data from manufacturing equipment or fleet vehicles to predict failures before they occur.

• Real Example: A logistics firm cut unplanned downtime by 22% and reduced parts inventory costs by 15% during the pilot.
• The ROI Fix: Our pilot costs are covered by the value of avoided downtime and maintenance savings. You pay a percentage of the demonstrated cost avoidance only after the pilot proves the ROI.

Automate the extraction and classification of data from invoices, contracts, or application forms, eliminating manual data entry.

• Real Example: A financial services provider processed 50,000 loan documents monthly, achieving 99% accuracy and reducing processing time from 10 minutes to 30 seconds per document.
• The ROI Fix: The pilot is funded by the labor cost savings it generates. Fees are triggered only after processing costs fall below a predefined threshold.

Use an AI control tower to optimize inventory levels, shipping routes, and supplier allocations in real-time based on demand signals and disruption alerts.

• Real Example: A retailer reduced excess inventory by 18% and improved on-time in-full (OTIF) delivery by 12% during a volatile quarter.
• The ROI Fix: The pilot's success is measured by reduced carrying costs and improved service levels. Our compensation is a share of the hard-dollar savings verified in your P&L.

Deploy models that analyze historical CRM data and external signals to prioritize sales leads most likely to convert, increasing sales team productivity.

• Real Example: A B2B software company increased its sales-qualified lead conversion rate by 28% and reduced lead follow-up time by 40%.
• The ROI Fix: We align our fees to the incremental revenue generated from the uplift in lead conversion, providing a clear, attributable return on the AI investment.

Implement machine learning models to analyze transaction patterns in real-time, identifying fraudulent activity with higher accuracy than rule-based systems.

• Real Example: A fintech platform reduced false positives by 60% and caught 15% more sophisticated fraud attempts during the pilot, directly protecting revenue.
• The ROI Fix: Our pilot costs are offset by the value of fraud prevented. We share in the savings from reduced fraud losses and operational review costs only after they are realized.

A global manufacturer faced $12M in annual expedited freight costs due to reactive logistics. Our Zero-Cost Pilot deployed an AI-driven dynamic orchestration agent that integrated data from carriers, warehouses, and production lines.

• Outcome: Achieved a 23% reduction in premium freight within the first quarter, generating $2.8M in savings before any fees were incurred.
• The AI autonomously re-routed shipments in real-time based on weather, port congestion, and capacity, stabilizing operations.

A mid-sized law firm spent over 15,000 associate hours annually on contract review and e-discovery, creating a capacity bottleneck. We piloted a document intelligence AI that automated data extraction and clause analysis from unstructured legal documents.

• Outcome: The AI processed 74% of routine contract reviews autonomously, freeing up 11,000+ billable hours for higher-value work in the first six months.
• Fees commenced only after the value of recovered billable hours exceeded the pilot's operational costs, providing immediate, verifiable ROI.

An automotive parts supplier experienced unplanned downtime costing $500k per incident. Our pilot deployed an Edge AI sensor network with real-time inference to predict equipment failures.

• Outcome: The system provided 14-day advance warnings for critical failures, reducing unplanned downtime by 42% in the first four months.
• This translated to $850k in avoided losses from production halts and maintenance overruns, creating a clear ROI threshold before the engagement converted to a full contract.

A SaaS company with a 12% annual churn rate needed to protect its recurring revenue stream. We launched a predictive analytics pilot using behavioral data to identify at-risk customers and trigger personalized retention workflows.

• Outcome: The pilot identified 90% of likely churn events 30 days in advance, enabling proactive saves that reduced churn by 3.2 percentage points.
• This retained $1.2M in annual recurring revenue (ARR) within the pilot window, creating undeniable financial justification for scaling the solution.

A national retailer struggled with generic marketing, achieving only a 1.5% email conversion rate. Our Zero-Cost Pilot implemented an agentic commerce AI that built individual customer models to personalize product recommendations and promotions in real-time.

• Outcome: Conversion rates increased to 4.7% and average order value rose by 18% during the pilot period.
• The incremental revenue directly attributed to the AI exceeded $300k, crossing the ROI threshold and triggering the performance-based fee structure.

A financial services firm dedicated a team of 12 analysts to manual monthly reporting, prone to errors under tight deadlines. We piloted a neuro-symbolic AI system that automated data aggregation, validation, and draft generation for regulatory filings.

• Outcome: The AI reduced report generation time by 70% and eliminated 100% of manual data entry errors.
• This saved over 800 person-hours per month, allowing the team to shift to strategic analysis. The quantifiable labor savings formed the basis for the ROI calculation that initiated our fees.