Don’t just monitor operations. Run them with agents.
Unite order-to-delivery data, company rules, and the systems you already use in one working layer. ajan.io helps you build AI agents that spot risks, check data, notify teams, and take action within defined permissions.
No credit card required.
Today's deliveries· Tuesday · 08:40
Sample scenarioPick an order to see the agent's reasoning and action plan.
SP-4821 · Ege Building Supply
Why?
The assigned truck returns 2 hours late from its previous run; the delivery window will be missed.
Based on: SLA policy · corporate customer, same-day delivery
Plan the agent prepared
- Reassign to the free truck at the Gebze depot
- Open a task to move dispatch up to 11:30
- Draft an updated delivery time for the customer
- Orders
- Shipments
- Warehouse
- Stock
- SLA
- Field
- Exceptions
As operations grow, tracking load doesn’t have to
Turn scattered data into operational decisions.
Logistics teams track orders, stock, vehicle plans, delivery dates, field crews, and customer expectations at once. ajan.io doesn’t just put that on one screen. Agents check the right sources, evaluate risk, and can start the next action.
See early
Spot delay, stock, or capacity risks before they become operational outcomes.
Decide faster
Evaluate the situation in one context instead of gathering data from separate systems.
Start the action
Notify the right team, create a record, or kick off an operations workflow.
Follow the process
See which stage work is in and which step is waiting on a human decision.
When delay risk appears, what does ajan.io do?
- 01
Checks orders
Pulls upcoming deliveries from the connected operations system.
- 02
Identifies risks
Evaluates delivery dates, stock, vehicle planning, and operations data together.
- 03
Checks company rules
Retrieves SLA and priority policies from corporate knowledge sources.
- 04
Ranks critical orders
Surfaces the records the operations team actually needs to intervene on.
- 05
Builds an action plan
Prepares work for stock, transport, or customer communication.
Gets required approval
Presents critical changes for an authorized user’s decision.
- 07
Acts in systems
Creates related records or tasks after approval.
- 08
Tracks the outcome
Follows the related operation until the process completes.
Not just risk detection — operations management from risk to action.
Example use cases
Delay risk management
Reviews upcoming deliveries, flags risky orders, and builds an action plan.
Shipment exceptions
Classifies delays, address issues, or failed deliveries and starts the right process.
Stock control
Flags critical stock, links it to open orders, and notifies the right teams.
SLA tracking
Evaluates operations against company SLA rules and prioritizes at-risk records.
Warehouse operations
Summarizes missing, pending, or exception work and creates tasks.
Field operations
Analyzes daily field status and surfaces work teams need to watch.
Customer updates
Prepares status messages from operations data and starts outreach after approval.
Manager summary
Presents the day’s critical operations, risks, and pending decisions in one brief.
Who hands off the tracking?
One agent takes on the repeated checking work of people across operations. The decisions stay with them.
Operations planner
Morning risk scan, truck and delivery-window checks.
Warehouse lead
Compiling short items, pending dispatches, and exception lists.
Customer representative
A current, consistent answer to "Where is my order?"
Operations manager
The day's critical work, pending decisions, and end-of-day summary.
Where does the agent read, and where does it act?
The agent connects to the systems operations already runs on. You don't move data; the agent reads the relevant record and takes the permitted action in that system.
- Order managementOpen orders, delivery dates, customer priorities
- Transport and route planningTruck assignments, runs, estimated arrival
- Warehouse managementStock, counts, dispatch and return records
- ERPCustomer, contract, and billing information
- Policies and proceduresSLA rules, priority policies, instructions
- Email and messagingTeam notices, customer update drafts
Connections are set up through ready integrations, MCP servers, or your own API. Not every system has a ready connection; we assess setup with you first.
The agent prepares; the team makes the critical call
You decide which actions run automatically and which wait for approval. The split below is a common starting setup for operations teams.
The agent does on its own
- Scans orders, stock, and truck data at set intervals
- Ranks risky records with the reason
- Opens check tasks for warehouse and field teams
- Prepares the end-of-day and manager summaries
Waits for your approval
- Truck or route changes
- Delay notices sent to customers
- Updating a delivery date
- Extra runs that add cost
Example chat prompts
ops-controlSample scenario
- Which orders have the highest delay risk today?
- Show deliveries at risk because of stock.
- Summarize critical operations in the Istanbul region.
- Create an action plan for these three orders and prepare it to send to the teams.
Not one AI feature — a working system
Work in your industry runs on the same ajan.io architecture.
Your company knowledge
Lets the agent know your company and your rules.
In logistics:SLA policy, priority rules, warehouse instructions
AI agents
Evaluate information and decide what work to do next.
In logistics:Delay-risk agent, customer status agent
Integrations
Pull data from existing systems and take permitted actions.
In logistics:Order, route, warehouse, and ERP connections
Workflows
Manage multiple steps, conditions, and waits in one process.
In logistics:Morning scan from risk to action
Human approval
Keeps critical decisions with the right person.
In logistics:Approval for truck changes and customer notices
Governance
Keeps access, usage, and AI costs under control.
In logistics:Access and usage by region and team
Knowledge + decision + action + process. One platform.
Not just AI chat — a layer that runs work
| AI chat only | ajan.io |
|---|---|
| Answers a question | Finds knowledge, evaluates, and advances the work |
| Works from user-provided context | Uses company knowledge and system context |
| Generates text | Can act in systems |
| Ends in one interaction | Can start multi-step workflows |
| The user tracks progress | Can keep process state |
| Fully manual or fully automatic | Can require human approval at critical points |
| Model-centric | Work-process-centric |
Let your team track less and run more operations.
Hand a large share of gathering, checking, reporting, and exception tracking to agents. Your operations team can focus on preventing delays, managing capacity, and improving customer experience instead of routine follow-up.
First agent: the morning risk scan
Don't hand over all of operations at once. Start with one check your team does by hand every morning, and widen the scope as the agent earns trust.
- 1
Upload the rules
Add your SLA policy and priority rules as knowledge sources.
- 2
Connect order data
One connection that can read open orders and the truck plan is enough.
- 3
Schedule the scan
Each morning the agent sends risky orders with reasons; actions open only with approval.
Questions logistics teams ask
What people ask most before connecting operations to an agent.
All FAQs
If your system has an API it can be defined as a custom integration; systems that offer an MCP server connect directly. For systems without a ready connection, we assess setup with you.
Create the first agent for your operations today.
Start free · No credit card required