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Agentic AI & Intelligent Automation
Enterprises are experimenting with AI, yet few can turn pilots into repeatable impact. NowVertical turns experimentation into execution with governed Agentic AI systems that think, act, and deliver measurable outcomes. We orchestrate autonomous workflows that plug into existing processes — enabling faster decisions, precision automation, and accountable, audit-ready actions across the business.
Leveraging Agentic AI & Intelligent Automation for Scalable Enterprise Outcomes
At NowVertical, we deliver adaptive intelligence, scalable automation, and safe, compliant outcomes.
60%
Optimization in through Agentic AI on Data Governance processes
40%
Optimization in through Agentic AI on Data Engineering processes
AI agents that don’t just advise — they act on your behalf, handling routine tasks and workflows end to end.
Every decision is transparent, controlled, and fully auditable to meet enterprise risk and compliance standards.
AI working alongside teams, amplifying expertise rather than replacing it to accelerate output and accuracy.
Agentic systems that monitor performance in real time and self-improve without manual intervention.
The Enterprise Journey
Most enterprises are already on the Agentic AI journey—past exposure and curiosity, and into pilots, copilots, and early commitments. But while 78% reach this exploratory stage, only 5% progress to the AI Flywheel, where adoption becomes systemic, compounding, and genuinely transformative.
Exposure
Initial awareness of agentic AI and its emerging potential for the enterprise.
Curiosity
Exploring possibilities, asking questions, and seeking to understand where AI could add value.
Commitment
Aligning intent, resources, and sponsorship to begin a focused AI journey.
Minimum Viable Agent
Developing a small, low-risk agent that proves concept and establishes early value.
Activation
Moving from prototype to real use by integrating the agent into live environments and workflows.
Horizontal & Vertical Scaling
Extending successful agents across teams, processes, and complexity levels to amplify impact.
Validation
Demonstrating measurable value, building confidence, and establishing repeatable success patterns.
Workflow Re-Invention
Redesigning processes around agent capabilities rather than simply enhancing existing ways of working.
Business Model Re-Invention
Evolving products, services, and revenue models to harness AI as a core strategic driver.
- Initial AI pilots
- Technology exploration
- Proof of concepts
- Scaling difficulties
- Governance challenges
- Cost barriers
- Workflow reinvention
- Business model transformation
- Sustainable competitive advantage
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NowUnlock Use Cases
Claims often involve multiple parties, providers, and documents, which traditional systems cannot easily manage. This creates long processing times, high error rates, and customer dissatisfaction.
- Analyse documentation and images using AI.
- Cross-check claims against policy coverage.
- Coordinate service providers, adjusters, and claimants.
- Detect fraud patterns and maintain compliance.
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Scaling account management is difficult when churn risks and growth opportunities rely on manual monitoring and fragmented insights. This leads to missed upsell chances and delayed intervention for at-risk accounts.
- Monitor usage, engagement, and health scores.
- Detect early churn signals and expansion opportunities.
- Automate outreach, recommendations, and routine tasks.
- Coordinate proactive interventions across teams.
Enterprises in regulated or high-volume industries often struggle with customer requests and transactions that span multiple departments. Siloed systems make it hard to deliver seamless service and ensure compliance.
- Route and process requests across products and channels.
- Coordinate complex investigations and multi-team responses.
- Automate service documentation and compliance checks.
- Monitor anomalies and trigger alerts in real time.
Traditional rule-based systems fail to keep pace with increasingly sophisticated fraud tactics, generating false positives that consume investigator time and miss coordinated attacks.
- Monitor transaction patterns in real time across systems.
- Correlate signals to identify subtle, multi-account fraud patterns.
- Automate investigation packages and audit trails.
- Trigger coordinated response actions across departments.
Managing long and complex sales cycles with multiple stakeholders, approvals, and solution configurations often overwhelms traditional CRM systems. This results in delays, fragmented communication, and lower win rates.
- Analyse past deal patterns to identify success factors.
- Coordinate activities and communications across sales teams.
- Generate tailored proposals and documentation automatically.
- Track competitive intelligence and optimise pipeline forecasts.
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Assess When to Choose Each Approachments
- Processes require decision-making
- Workflows involve multiple stakeholders
- Context and variability are high
- Strategic outcomes are the goal
- End-to-end process automation
- RPA handles structured tasks
- AI manages decision points
- Maximum efficiency is needed
- High-volume repetitive tasks
- Rules are well-defined
- Speed and accuracy are critical
- Quick ROI is prioritized
- Complex sales orchestration
- Dynamic customer service routing
- Adaptive fraud detection
- Strategic decision support
- Invoice processing & data entry
- Report generation & distribution
- System migrations & updates
- Compliance & audit tasks
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