Agree on one structure
Record source, region, category, available offer terms, and check time. Begin with a few pages.
For multi-site companies and analytics teams
Fresh network data in your own storage.
As regions and product lines grow, manual checks cannot keep up. Run collection regularly on your server and send results to the corporate storage your analysts already use.
Data belongs in working storage, not a chat thread
Departments check the same pages and email spreadsheets to each other. Agree on a common external-data structure and deliver updates to your database. Analysts can combine it with internal metrics in familiar tools.
Your agent networkScale to fit the task
Agent 1Region 1
Agent 2Region 2
Agent NRegion N
Corporate storageResults beside your analytics
Turn a task into a process
Start with a small sample. Then control the rules, frequency, and result.
Choose execution and storage
Assign collection to an agent. Connect a local database for records and, if needed, S3-compatible storage for files.
Bring the data into analysis
Schedule collection and quality checks. After delivery, join external data with internal metrics using agreed keys.
What gets easier
Collection, storage, and delivery become one clear workflow.
One processing pattern
Departments receive the same field structure and a clear check time.
Resources sized for your load
Choose a server and plan its capacity around collection frequency. Source restrictions and plan conditions still apply.
History in your environment
Results and record changes stay on the agent, while your team defines rights for the corporate recipient.
Results stay in your system.
Use your database through a suitable connector, local files, or a handler in your environment. For private recipients, an administrator configures approved network access or an SSH tunnel.
Agent
Corporate database
S3-compatible storage
CSV / JSON / XML
Before starting
How should storage be arranged?
Databases receive tabular records; an S3 connection handles files. Join with internal sales after delivery to your analytics system. Mirroring results to the platform is enabled separately.
How data is separatedWhat should be agreed in advance?
- Collection frequency and acceptable source load
- Keys used to join analytical records
- Who maintains quality, servers, and backups
Can a powerful server bypass a site's limits?
Your agent gives you control over compute and storage. It does not waive access rules, source limits, or the need for a sensible request rate.
Can I read an export directly from the agent?
Yes. The agent prepares its own exports. Configure external access separately with protected HTTPS and tokens; do not expose its database to the internet.
Test your workflow on one source.
First confirm that data reaches the intended recipient. Then add a schedule and more sources.