Build automated workflows using AI agents to eliminate repetitive tasks and cut cycle time 50–70%.
Operations, Finance, and IT leaders who have identified specific workflows with high manual effort and want to automate them with AI agents. Ideal for organizations that have completed an AI Readiness Assessment or have clear automation targets.
50–70%
Faster processing from start to completion in automated workflows
60–80%
Reduction in manual data entry, routing, and exception handling
40–60%
Fewer mistakes from manual processing and data entry
30–50%
Lower operational costs through automation and efficiency
Deployed, tested, and integrated with your systems
Agent decision logic, human-in-the-loop checkpoints, and error handling
API integrations with ERPs, CRMs, databases, and business systems
Testing framework and dashboards to track agent performance and accuracy
User guides, training materials, and adoption support
Extract data from invoices, match to POs, route for approval, and post to ERP. Handles exceptions and learns from corrections.
Impact: 70% faster processing, 50% fewer errors, 60% cost reduction
Collect documents, verify information, run background checks, create accounts, and trigger welcome sequences—all automated with human review gates.
Impact: 65% faster onboarding, 40% better activation rates
Route orders to optimal fulfillment centers, allocate inventory, generate shipping labels, and handle exceptions (backorders, substitutions).
Impact: 50% faster fulfillment, 30% lower shipping costs
Classify tickets, route to correct team, retrieve knowledge base answers, and escalate complex issues—reducing L1 ticket volume by 60%.
Impact: 60% faster resolution, 50% lower support costs
Extract key terms, flag non-standard clauses, route for legal review, and populate contract management systems.
Impact: 80% faster contract processing, better risk visibility
Analyze equipment data, predict maintenance needs, schedule technicians, order parts, and update work orders automatically.
Impact: 30% less downtime, 25% lower maintenance costs
Map current workflow, identify decision points, document exceptions, and baseline performance metrics. We interview users and analyze process data to understand the full workflow.
Design agent logic, build integrations, create human-in-the-loop checkpoints, and deploy to production. We test with real data and iterate based on feedback.
Monitor performance, measure accuracy, track business metrics, and optimize. We provide dashboards and ongoing support to ensure the workflow delivers expected ROI.
3–8 weeks
Per workflow, depending on complexity and integrations
8–16 hours
Total stakeholder time for interviews, testing, and training
Timeline factors:
$25,000–$60,000
Per workflow, based on complexity and integration requirements
Each workflow is designed to improve specific Universal Chart of Accounts process KPIs:
Cycle time
Cost per transaction
Error rate
Throughput
First-pass yield
SLA adherence
Processing time
Manual effort hours
Exception rate
Customer satisfaction
Employee productivity
Data accuracy
We use modern agent frameworks and integrate with your existing systems. Tool-agnostic approach with preference for open-source and API-first solutions.
Risk: AI agents make incorrect decisions or generate false information, leading to business errors.
Safeguard: Evaluation harnesses with accuracy thresholds, human-in-the-loop checkpoints for critical decisions, retrieval-augmented generation (RAG) to ground responses in your data, and continuous monitoring with alerting.
Risk: System integrations fail, causing data loss or workflow interruptions.
Safeguard: Robust error handling, retry logic, transaction rollback capabilities, audit logging, and fallback to manual processes when systems are unavailable.
Risk: Users resist the new workflow or don't trust the automation, leading to low adoption.
Safeguard: Comprehensive training, clear communication of benefits, gradual rollout with feedback loops, and transparent monitoring so users can see agent decisions and override when needed.
Challenge: AP team processing 500+ invoices monthly, taking 15 minutes each with high error rates from manual data entry.
Solution: Deployed invoice processing agent that extracts data, matches to POs, routes for approval, and posts to ERP. Human review only for exceptions.
Impact: 70% faster processing (15 min → 4.5 min), 50% error reduction, $120K annual labor savings, team freed up for strategic work.
Challenge: Customer onboarding taking 5–7 days with manual document collection, verification, and account setup.
Solution: Built onboarding agent that collects documents, verifies information, runs checks, creates accounts, and triggers welcome sequences—all automated with approval gates.
Impact: 65% faster onboarding (7 days → 2.5 days), 40% better activation rates, improved customer satisfaction, scalable to 10X volume without adding headcount.
We use multiple safeguards: evaluation harnesses that test agent accuracy on historical data, human-in-the-loop checkpoints for critical decisions, retrieval-augmented generation to ground responses in your data, and continuous monitoring with alerting when confidence scores drop. We also design workflows to fail gracefully and route exceptions to humans.
We design agents to be adaptable. The workflow logic is documented and version-controlled, making updates straightforward. For highly dynamic workflows, we can build self-learning agents that adapt to patterns, or we can provide ongoing support for updates (typically $2–5K per change).
No. Agents integrate with your existing ERPs, CRMs, and business systems via APIs. We work with what you have and only recommend new systems if there's a clear benefit. The agent layer sits on top of your existing infrastructure.
We design exception handling into the workflow from day one. Agents are trained to identify when they're uncertain and route to humans. We also build escalation paths, retry logic, and fallback procedures. During implementation, we test with real exception data to ensure robust handling.
RPA automates repetitive tasks by mimicking human clicks and keystrokes. AI agents make intelligent decisions, understand context, handle unstructured data, and adapt to variations. Agents are better for workflows requiring judgment, natural language understanding, or dealing with exceptions. We can combine both approaches when appropriate.
Yes. We recommend starting with a pilot workflow (typically 2–3 weeks, $15–20K) to prove the concept and build confidence. If successful, we scale to additional workflows. Many clients start with one workflow and expand to 3–5 workflows over 6–12 months.
We offer monitoring and maintenance packages ($2–5K/month) that include performance dashboards, accuracy tracking, optimization updates, and support for workflow changes. We also provide training for your team to manage and extend workflows independently.
Book a 20-minute fit call to discuss your workflow challenges and see if agent automation is right for you.
Last updated: November 2025