# Agentic workflow automation > We rebuild back-office processes as workflows. Fixed steps stay as code, agents handle the steps that need judgment, and people approve the exceptions. - Page: https://www.ninalabs.ai/services/workflows/ - Publisher: Nina Labs AI LLC - Updated: 2026-10-07 ## Definition An agentic workflow is a process where fixed rules run as code, a model handles the steps that need reading or judgment, and people approve the cases the rules do not cover. ## What you get - A process map with volumes, handling times and the workarounds people use today - The workflow in code, with each step marked as rule, model or person - Approval points and an exception queue that shows the case, the sources and the agent's reasoning - Integration with your systems of record - Weekly reports on cycle time, straight-through rate, accuracy and cost per case ## Typical use cases - **Document intake:** Classifies claims, applications and contracts, extracts the fields and routes each case to the right queue. - **Order and invoice processing:** Reads orders and invoices in any layout, checks them against master data and posts the clean ones. - **Customer onboarding and KYC:** Collects documents, checks them against your policy and sanctions lists, and prepares the file for a compliance officer. - **Month-end reconciliation:** Matches transactions across systems, explains the breaks it finds and drafts the journal entries for review. - **Contract review:** Compares incoming contracts with your playbook and marks each clause that needs a lawyer. - **Questionnaires and RFPs:** Drafts answers to security questionnaires and RFPs from approved sources, with a citation for each answer. ## Not every step needs a model A typical back-office process has 20 to 40 steps. Most of them are rules: look up a vendor, check a threshold, write a record. A few need judgment: read a scanned document, decide which policy applies, write to a customer. We keep the rules as code and put a model only where judgment is needed. The result is a workflow that is cheaper to run, faster, and easy to explain to an auditor. ## How we build it 1. **Map the process as it runs today**, including the spreadsheets, side emails and workarounds. 2. **Mark each step** as rule, model or person. Then estimate the volume and the error cost at each step. 3. **Build on a durable workflow engine**, so long-running cases survive restarts, retries and approvals that take days. 4. **Add the exception queue** before the automation. People must be able to see and fix every case the system cannot finish. 5. **Run old and new side by side** on the same cases until the numbers agree. ## What you get each week A short report with cycle time, straight-through rate, error rate and cost per case. Each week also shows the cases that went to people and why. That list tells us what to automate next. ## Stack we use Temporal, AWS Step Functions, Azure Durable Functions, Microsoft Agent Framework, Google ADK, Copilot Studio, Gemini Enterprise, Amazon Bedrock AgentCore ## What we measure - Cycle time from intake to close - Straight-through rate, which is the share of cases with no human touch - Error rate found in review and after close - Cost per case compared with the baseline ## Frequently asked questions ### Why not let one agent run the whole process? Most processes are mostly rules. Rules in code are cheaper, faster and easier to audit than a model that has to follow them. We use a model only where a step needs reading, judgment or language. ### What happens to cases the workflow cannot handle? They go to an exception queue. A person sees the case, the source documents and what the agent found, then decides. Each decision becomes a test case for the next release. ### Do you replace our current automation tools? Not by default. If you already run a workflow or RPA platform, we add the model steps to it where that works and replace only the parts that block the result. ## Related services - [AI agents in production](https://www.ninalabs.ai/services/agents/) - [Evals, security and AI governance](https://www.ninalabs.ai/services/evals-governance/) ## Contact Talk to an engineer through the [contact form](https://www.ninalabs.ai/contact/) or by email at contact@ninalabs.ai.