AI Engineering
Intelligent Automation
Automate the processes that traditional tools could not handle, those full of emails, attachments and judgement calls, by combining reliable workflow rules with AI where interpretation is needed.
Introduction
Rules where possible, AI where necessary
Classic workflow automation excels at predictable steps: if a field equals X, route to Y. Real business processes are messier. Requests arrive as free-text emails, documents come in different layouts, and exceptions are common.
Intelligent automation adds AI at the points where a human would normally have to read, interpret or decide. Everything else stays deterministic, which keeps the process fast, auditable and inexpensive to run.
Business challenges
The problems this solves
Manual triage of inbound work
Staff spend hours reading emails and attachments simply to decide where each request should go.
Re-keying between systems
Data is copied from documents and portals into business systems by hand, introducing delays and errors.
Exceptions break automation
Existing scripts or RPA bots stop at the first unexpected format, leaving queues of failed items.
Little visibility of process health
Managers cannot easily see backlogs, bottlenecks or turnaround times across the workflow.
Proposed approach
How we approach it
We map the process first and automate second, so that the automated version is simpler than the manual one.
- Document each step, its inputs, decision rules and exception paths with the people who run it
- Remove steps that exist only because of past system limitations
- Use deterministic rules for predictable logic and AI only for interpretation tasks
- Send low-confidence AI decisions to a review queue rather than guessing
- Instrument every step so throughput and exceptions are visible on a dashboard
Core capabilities
What we deliver
Intake and classification
Read emails, forms and messages, identify the request type and priority, and route accordingly.
Document understanding
Extract data from invoices, purchase orders, IDs and forms with confidence scores per field.
Workflow orchestration
Coordinate steps across systems with retries, timeouts, parallel branches and approvals.
Validation and matching
Cross-check extracted data against master records, purchase orders or policies.
Human review queues
Purpose-built review screens that show the AI’s suggestion, confidence and source document side by side.
Process analytics
Live views of volumes, cycle times, automation rates and exception reasons.
Use cases
Relevant use cases
Examples of where this capability is commonly applied.
Accounts payable intake
Capture invoice data, match it to purchase orders and goods received, and route discrepancies for review.
Customer onboarding
Validate submitted documents, create accounts across systems and trigger welcome communications.
Claims and returns processing
Classify claims, check eligibility rules and prepare a recommended decision for an assessor.
Order entry from emails
Convert emailed orders and spreadsheets from customers into sales orders in the ERP.
Technology considerations
Choosing the right technology
We can extend workflow tools you already own or build a lightweight orchestration service where existing tools fall short.
Orchestration
- Workflow engines
- Message queues
- Scheduled jobs
- Webhooks
AI components
- Document AI / OCR
- LLM classification
- Entity extraction
Systems
- ERP
- CRM
- Email platforms
- Document management
Implementation
Implementation process
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1
Process discovery
Map the current workflow and measure volumes, effort and error points.
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2
Target design
Design the simplified future process and decide where AI adds value.
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3
Build in slices
Automate one segment end-to-end before moving to the next.
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4
Parallel run
Run automated and manual processing side by side to compare results.
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5
Operate and refine
Monitor exceptions and tune rules and models as patterns change.
Explore more
Related services and solutions
Business Process Automation
Streamline approvals, intake and back-office routines with automation and AI assistance.
Learn more about Business Process AutomationIntelligent Document Processing
Extract, validate and route data from invoices, forms and contracts automatically.
Learn more about Intelligent Document ProcessingWorkflow Orchestration
Coordinate multi-step processes across systems, teams and AI services reliably.
Learn more about Workflow OrchestrationAI Agent Development
Goal-oriented AI agents that plan tasks, use your tools and escalate to people when needed.
Learn more about AI Agent DevelopmentFAQs
Frequently asked questions
Answers to the questions we hear most often. If yours is not covered here, our team is happy to talk it through.
Robotic process automation mimics clicks in user interfaces and struggles with variation. Intelligent automation integrates through APIs where possible and uses AI to interpret unstructured inputs, so it handles real-world variety more gracefully.
It typically shifts their focus from data entry and sorting to handling exceptions, improving the process and serving customers. Human review remains an essential part of well-designed automation.
Each extracted field carries a confidence score. Low-confidence items go to a review queue, and validation rules catch inconsistencies before data reaches your systems of record.
Yes, and we recommend it. Automating a single high-volume document type or request category proves the approach and builds the shared components for the next step.
Which process would you automate first?
Walk us through a workflow your team finds repetitive and we will map where automation and AI could help.
