Modern workflow automation combines deterministic rules with AI agents that can interpret unstructured information, work with approved business knowledge and initiate controlled actions across connected applications.
INERTIKA designs and implements rules-based workflows, platform-native automation and AI agents across Microsoft, Salesforce, HubSpot and service management environments. Every solution includes defined ownership, access controls, exception handling, human review, monitoring, documentation and operational support.
Before configuration begins, we define how the process operates, where decisions are made and which actions require rules, AI assistance or human approval.
Workflow trigger and completion conditions
Participants, roles and responsibilities
Required inputs and expected outputs
Decision rules and approval thresholds
System and data dependencies
Manual and AI-assisted process steps
Exception and escalation paths
Access, audit and acceptance criteria
Result: a complete workflow specification covering process steps, decision rules, ownership, exceptions and automation boundaries.
We configure the workflow in the appropriate platform and connect it to the applications and data required to complete the process.
Forms, fields and workflow states
Routing and assignment rules
Approval sequences and thresholds
Notifications, reminders and escalations
Microsoft Power Automate and Azure Logic Apps
Salesforce Flow and HubSpot Workflows
Jira Automation and Freshservice configuration
API, webhook and database connections
Role-based access and environment configuration
Result: a working automated workflow configured for its users, systems and operating requirements.
We design and configure AI agents for workflows that require interpretation of unstructured information, access to approved business knowledge or coordinated actions across applications.
Agent purpose, instructions and operating boundaries
Approved knowledge sources and grounding rules
Access permissions and data controls
Tools, connectors and permitted system actions
Customer, prospecting, data and internal knowledge agents
Document extraction, classification and summarisation
Confidence thresholds and fallback procedures
Human approval before high-impact actions
Handoff to sales, service and operational teams
Agent monitoring, logging and cost controls
Result: AI agents that perform defined work inside controlled business processes, with access boundaries, traceable actions and human intervention where required.
Rules-based workflows and AI agents must remain predictable, secure and supportable after go-live.
Data validation and duplicate-prevention rules
Timeout, retry and escalation procedures
Manual review and override paths
Functional and end-to-end workflow testing
Agent-response and action testing
Knowledge-grounding and permission testing
User acceptance testing
Workflow and agent monitoring
Audit records and action history
Administrator documentation and support runbooks
Knowledge transfer and post-launch stabilisation
Project Outputs
Current and target workflow maps
Workflow specification
Decision and approval matrix
Roles and ownership matrix
Exception and escalation catalogue
Agent specification and instruction set
Knowledge-source and access map
Tools and permitted-action matrix
Human-approval and handoff rules
Agent evaluation and test set
Configuration and deployment record
Administrator guide and support runbook
Result: controlled and documented automation with visible exceptions, defined ownership and human review for sensitive decisions and system actions.
Controlled Automation Ready for Operations
Business processes automated through consistent rules and AI agents, with clear ownership, visible status, traceable actions and documented exception handling.
What Changes in Practice
Fewer manual steps and repeated data entry
Consistent approval, routing and escalation rules
AI agents handling defined research, classification and support tasks
Human oversight for sensitive decisions and high-impact actions
Clear ownership of tasks, agents and exceptions
Visible workflow status and processing history
Traceable decisions and agent actions
Less dependence on email, spreadsheets and manual follow-up
Documented procedures for support and future changes
For implementation and migration of the underlying applications, see Enterprise Platforms. For connections between systems, APIs and data, see Systems Integration.
Planning a Workflow Automation or AI Agent Project?
