Trigger
Agent
Approval
Human approval required before posting or customer-facing action.
Agentic AI and Workflow Automation Designed Around Real Business Processes
Automation creates value when it removes friction from an end-to-end process - not when it adds another isolated bot, dashboard or tool for employees to manage.
Contetra helps organisations identify, design and implement AI-enabled workflows across finance, reporting, sales, operations, marketing and project management. We combine process understanding, control design, systems integration and agentic AI to automate work that currently moves between people, spreadsheets, email, ERP, CRM and other business applications.
Our approach keeps human judgement where it matters. AI agents can gather information, analyse, draft, route, reconcile, monitor and trigger actions, while defined approvals, access controls, validations, audit trails and exception paths protect the business process. Where an agent touches the books, the control questions are the same as they would be for a person: who prepares, who approves, whether those can be the same, and what evidence an auditor will accept for an entry a machine has drafted.
Start with a high-friction process and a measurable outcome
Map the current workflow, quantify the effort and risk, and identify the most defensible automation design.
What agentic automation can change
From task automation to process execution
Instead of automating a single click, agents can coordinate multiple steps, systems, documents and decisions within a governed workflow.
From manual follow-up to exception management
Routine checks, reminders, status updates and data gathering can run automatically, allowing teams to focus on exceptions and judgement.
From static reporting to continuous monitoring
Agents can collect data, test conditions, investigate variances, draft commentary and escalate issues based on defined rules.
From fragmented knowledge to guided action
Policies, SOPs, contracts and historical decisions can be made searchable and usable within workflows, subject to permissions and source controls.
Functions we automate
Finance and accounting
Invoice processing, reconciliations, close tasks, collections, cash reporting, variance analysis, audit schedules, approvals and recurring management reporting.
Sales and customer workflows
Lead enrichment, qualification, routing, follow-up, meeting summaries, CRM updates, proposal preparation and pipeline reporting.
Marketing
Campaign workflows, content operations, reporting, lead hand-offs, research, data enrichment and recurring performance summaries.
Operations and procurement
Vendor onboarding, purchase workflows, document checks, inventory alerts, service requests, exceptions, compliance tasks and operating reports.
Projects and task management
Status collection, dependency monitoring, risk and issue updates, meeting actions, resource reporting, reminders and PMO packs.
Knowledge and support
Enterprise search, policy assistants, SOP guidance, ticket triage, response drafting and escalation using approved internal sources.
Our automation design principles
Process before platform
Map the current process, exceptions, controls, owners and expected outcome before selecting tools or building agents.
Human-in-the-loop by design
Define where humans approve, review or override, rather than adding oversight after the workflow has been built. In finance workflows this means maker-checker survives automation. An agent may prepare, match and route, but posting, payment release and customer-facing commitments stay with a named approver.
Secure access and least privilege
Agents should only access the systems, data and actions required for their role, with credentials and permissions governed appropriately.
Traceable inputs and actions
Retain sources, prompts, validations, versions, decisions and action logs where business risk requires reviewability.
Exception-first operating model
Design queues, thresholds, escalation and fallback paths so teams know exactly what happens when confidence or data quality is insufficient.
Measurable value
Baseline cycle time, manual effort, error rate, leakage, response time or control failure before implementation and track the change after deployment.
How we implement automation
Step 1 · Opportunity assessmentIdentify high-volume, high-friction or high-risk workflows and score them for feasibility, value, control requirements and data readiness.
Step 2 · Process and control designMap steps, roles, systems, inputs, outputs, business rules, exceptions, approvals and audit requirements.
Step 3 · Solution architectureSelect the right combination of workflow tools, APIs, RPA, AI models, knowledge retrieval, agent orchestration and human interfaces.
Step 4 · Proof of valueBuild a controlled pilot using representative data and clear acceptance criteria before expanding scope.
Step 5 · Integration and deploymentConnect systems, configure monitoring, complete security and user testing, document the workflow and train owners.
Step 6 · Govern and improveTrack outcomes, incidents, model or rule changes, user feedback, exceptions and new automation opportunities.
Typical technology environment
Technology choices should follow the use case, enterprise architecture and security requirements. Relevant environments may include:
Microsoft Power Automate, Power Platform and Copilot Studio
n8n, Make and other workflow orchestration platforms
UiPath and other RPA or document-processing tools
Azure OpenAI, AWS Bedrock and approved enterprise AI services
ERP and CRM systems including SAP, Microsoft Dynamics, Oracle, NetSuite, Odoo, ERPNext, Salesforce, HubSpot and Zoho
Databases, document repositories, email, collaboration, project and reporting tools
Custom APIs, retrieval-augmented generation and governed agent frameworks where appropriate
Governance controls we build in
- Human approval checkpoints for material actions.
- Role-based access and separation of duties.
- Source citation or evidence links where information is generated from documents.
- Validation rules, thresholds and confidence-based escalation.
- Action logs and traceability for sensitive workflows.
- Testing against expected, edge and failure scenarios.
- Monitoring for workflow errors, model drift, data changes and unusual activity.
- Defined ownership for incidents, changes and periodic review.
Frequently Asked Questions
Explore in detail
Start here
Then execute across
Turn recurring work into a governed, measurable workflow
Bring one process that consumes time, creates delays or depends too heavily on individual follow-up. We will help determine whether AI, workflow automation or process redesign is the right answer.