Let Business Data Proactively Find the Right People

[n.01/04]> Data Bottlenecks

Operations teams spend much of their time not analyzing data but 'finding data' and 'moving data' — exporting from CRM, processing in Excel, taking screenshots for group chats. FIM One delivers data automatically to those who need it.

Copilot

//001

Data retrieval is daily manual labor

Every morning, operations staff perform fixed routines: log into CRM, filter by region/product line, export Excel, calculate period-over-period changes, create charts, screenshot or copy to documents, share in work groups. When holidays or travel interrupt, data broadcasts stop. This isn't analysis — it's data transport.

//002

Executive ad-hoc queries can't be answered instantly

'What was East China's signing amount last week?' 'How are the top ten clients' contracts progressing this month?' — these questions come up frequently in meetings. Operations need to return to their desk, open systems, pull data, and calculate before responding. By then, the meeting may have ended.

//003

Comprehensive business analysis requires merging multiple data sources

Sales data in CRM, customer complaints in ticketing, marketing spend in ad platforms, financial collections in ERP. Compiling a complete monthly business report means separately exporting from four or five systems, then manually merging and validating in Excel.

[n.02/04]> Intelligence Loop
[001]
Scheduled Data BroadcastsDaily at 9 AM (configurable), Agent auto-executes: pulls previous day's business data from CRM/database via connectors, aggregates by preset dimensions (region, product line, customer, amount, status), LLM generates analytical summary with key metrics, period comparisons, and anomaly flags, pushes to designated Feishu/WeCom groups as rich cards. Operations staff just review the push and investigate anomalies when needed.
[002]
Natural Language Instant QueriesOperations or managers @Agent in group chats: 'What was East China's signing amount last week?' 'Top 10 clients' contract progress this month?' 'Q1 regional collection completion rates?' Agent auto-converts questions to data queries, executes, and returns results. Supports follow-ups and drill-downs: 'Which ones are uncollected? What are the details?'
[003]
Multi-Source Data AggregationFor cross-system comprehensive analysis: Agent simultaneously pulls data from CRM, ticketing system, and financial system, processes in the built-in Python execution environment, and LLM generates comprehensive analysis reports.
[n.03/04]> Strategic Value
//001

Operations staff freed from data transport

Daily and weekly reports auto-generated and pushed. Team's attention shifts from 'how to get data' to 'what does data tell us.'

//002

Ask in chat, get results on the spot

Managers ask questions in group chats using everyday language, Agent responds instantly. No waiting for operations to return to their desk and manually query.

//003

Multi-source data auto-aggregated

No more separate exports from multiple systems and manual merging in Excel. Agent pulls cross-system data, processes and presents it in a unified way.

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