Stop moving data.
Start acting on it.
An AI agent that aggregates data across your systems on a schedule, detects anomalies before your team does, and builds reports without anyone having to pull them.
Why operations teams are still running on manual processes
Reports are built manually, every time
Someone pulls data from three systems, pastes it into a spreadsheet, formats it, and sends it. Every week. This is not analysis — it's data movement, and it costs you hours your team could spend on actual decisions.
Anomalies are found after the damage
A cost spike, a missed SLA, a reconciliation gap — noticed at the end of the month when the report comes out. By then the window to act has closed.
Process handoffs lose context
Task finishes in one system, someone has to manually trigger the next step in another. When it doesn't happen, nobody knows until someone complains. There's no thread connecting the steps.
Operational data lives in five systems, queryable in none
Finance is in one tool. Ops metrics in another. Customer data in a third. Getting a cross-functional view requires a person who knows all three — and that person is always busy.
From raw data to report, automatically
Scheduled data collection
The agent runs on a defined schedule — hourly, daily, weekly — and pulls data from every configured source. Databases, CRM, ticketing systems, spreadsheets. No human triggers it; no human has to remember to run it.
Cross-system aggregation and reconciliation
Data from multiple sources is joined, deduplicated, and reconciled against defined expectations. If numbers don't add up — a count mismatch, a missing record, a value outside tolerance — that's flagged before the report is built.
Anomaly detection and alerting
Metrics are evaluated against baselines and thresholds. Cost spikes, SLA breaches, inventory shortfalls, conversion drops — surfaced immediately, routed to the right person, with context about what changed and when.
Report generation and distribution
Structured reports built from the aggregated data — formatted for the audience, distributed to the right channel or inbox, filed to the right folder. The agent writes back to SharePoint, Confluence, or email automatically.
What the agent handles
Scheduled workflows
Cron-style or event-triggered execution. Set it once; it runs on schedule without manual intervention.
Multi-source aggregation
Pulls and joins data across databases, CRMs, ticketing systems, and spreadsheets in a single workflow run.
Reconciliation checks
Validates data against defined rules before reporting. Mismatches flagged and routed, not silently included.
Anomaly detection
Baseline-aware alerting on metrics that matter: cost, SLA, volume, conversion, inventory.
Report generation
Formatted reports written to SharePoint, Confluence, email, or Slack — in the format your audience expects.
Process chain tracking
Monitors multi-step workflows across systems. Stalled handoffs detected and escalated before they become missed deadlines.
Cross-functional views
Combines data from finance, ops, and customer systems into unified summaries — without a human as the join key.
Audit of every run
Every workflow run logged: what was pulled, what was computed, what was sent, what anomalies were found.
Reads from where your data lives
The agent connects directly to your databases, CRM, and collaboration tools. No ETL pipeline to maintain, no data warehouse to provision first.
View all integrations →
PostgreSQL
MySQL
Salesforce
Jira
SharePoint
Confluence
Slack
MS TeamsShow us a report your team builds manually
We'll set up the workflow live — connected to your data sources — and show you the aggregated output and anomaly detection it produces.