Process Automation
Intelligent Automation That Thinks Ahead Go beyond traditional RPA with AI agents that understand context, make decisions, and handle exceptions — automating up to 90% of complex business processes.
Delivery Snapshot
Purpose-built AI agent capabilities for process automation.
End-to-end coordination of multi-step business processes across departments, systems, and stakeholders with intelligent routing and escalation.
Context-aware decision-making that applies business rules, historical patterns, and real-time data to handle complex judgment calls automatically.
Automatic discovery and mapping of existing business processes from system logs, identifying bottlenecks, redundancies, and automation opportunities.
Seamless integration with existing RPA tools and bots, adding intelligence and exception handling to extend the reach of your current automation investments.
Smart approval routing that determines the right approvers, handles delegation, escalates stale requests, and tracks compliance requirements.
Intelligent resolution of process exceptions that would normally require human intervention, learning from past resolutions to handle new edge cases.
A structured path from signal ingestion to measurable production impact in process automation.
FlowAgent analyzes your existing workflows through process mining — mapping every step, decision point, and exception path to build a complete understanding of how work actually flows through your organization.
PHASE 01 / 03
AI agents take over routine tasks while learning to handle exceptions. Each agent specializes in a process stage — intake, classification, processing, validation — and collaborates to move work forward without bottlenecks.
PHASE 02 / 03
The system continuously monitors process performance, identifies new automation opportunities, and adapts to changing business rules — getting smarter and more efficient over time.
PHASE 03 / 03
See how FlowAgent solves critical challenges in process automation.
Manual invoice processing is slow, error-prone, and requires significant headcount to handle thousands of invoices monthly.
FlowAgent extracts data from invoices in any format, matches them to purchase orders, validates amounts, and routes for approval automatically.
Roughly 60-80% faster cycle times with improved accuracy, consistent with published IDP and RPA benchmarks; humans review exceptions.
Employee onboarding involves dozens of tasks across HR, IT, facilities, and compliance — leading to delays and inconsistent experiences.
AI agents orchestrate the entire onboarding workflow, from offer letter generation to system provisioning, ensuring nothing falls through the cracks.
Materially faster onboarding completion with every required step tracked and auditable, so tasks no longer fall through the cracks.
Claims processing requires manual review of complex documents, policy checks, and fraud detection — creating long settlement times.
FlowAgent reads claim submissions, validates coverage, flags anomalies for fraud review, and auto-approves straightforward claims.
Shorter average settlement time in line with automation benchmarks, with anomalies flagged for human fraud review rather than auto-paid.
Complex order fulfillment across multiple warehouses and suppliers requires constant coordination and exception management.
Agents manage the full order lifecycle — inventory checks, supplier coordination, shipping optimization, and customer communication.
Fewer order errors and faster, more reliable delivery as agents catch exceptions early and keep customers informed.
How specialized agents coordinate inside FlowAgent.
Inputs
Orchestration
Agents
Intake Agent
Receives and digitizes incoming requests and documents
Classification Agent
Categorizes and prioritizes work items by type and urgency
Processing Agent
Executes business logic and automates core tasks
Validation Agent
Verifies accuracy and compliance of processed outputs
Routing Agent
Delivers results and escalates exceptions as needed
Representative figures grounded in published process automation benchmarks.
Faster processing
70%
Report improved accuracy
90%
Of tasks technically automatable
60%
Typical payback period
12 mo
A representative FlowAgent scenario modeled on published industry benchmarks.
~70% faster processing
Representative outcome · benchmark-based
A representative operations team deploys FlowAgent to automate a high-volume, rules-plus-judgment workflow end to end. Grounded in Deloitte automation benchmarks and McKinsey automation-potential estimates, the scenario targets roughly 60-80% faster processing with improved accuracy, while humans manage exceptions.
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