Diwo
Diwo CatalystPlatform · Ask Your Data Anything

Your team asks.Your data answers.

Catalyst is the conversational analytics layer of Diwo. Every operator, analyst, and executive types a question in plain English; Catalyst runs the query, assembles the answer with charts and evidence, and stitches pinned cards into auto-generated dashboards and executive briefings.

Try Catalyst on your dataSee a conversationPlug in your warehouse. Ask. Get an answer.
Live: what operators ask Catalyst
Operator typing…
Which customers have the most repeat high-severity alerts?
Catalyst · query executed in 1.8s · 35 rows returned
01Ask

Start the day with a queue of questions.

Catalyst greets every user with a ranked list of recommendations — the questions worth asking right now, drawn from their use case and the current state of the data. Pick one, or type your own. Every conversation begins where analysis actually matters.
See how a regional bank seeded its Catalyst recommendations
Good Morning, Admin UserAU

Good morning, Admin

How can I help you today?
New Recommendations20
All28Client Engagement & Satisfaction7Client Revenue & Profitability7Risk & Compliance6
Client Engagement & Satisfaction7
4/19/2026
Prioritize Retention of High Net Worth Clients with Low Satisfaction
High Net Worth clients generating significant revenue may have low satisfaction scores or unresolved complaints, putting revenue at risk.
4/19/2026
Monitor Open Critical Risk Alerts on High-Balance Accounts
Open risk alerts with Critical or High severity on accounts with large balances represent significant financial exposure.
4/19/2026
Reduce Escalated Complaints by Improving Branch Channel Experience
Branch interactions may show higher escalation rates and longer durations compared to digital channels. Identifying root causes unlocks CSAT.
4/19/2026
Address Credit Card Fee Complaints Driving Low Satisfaction
Credit card fee inquiries and complaints appear frequently and may correlate with low satisfaction scores. Fee structure warrants review.
02Answer

A real answer — not another dashboard.

Catalyst returns a structured answer with Observations, Data, and Evidence tabs. Summaries sit on top; the raw rows and the reasoning sit one click away. Every assertion can be verified without leaving the conversation.
How a health system grounded every answer in evidence

Flag repeat high-severity alert customers for enhanced monitoring

2h ago
Query returned 35 rows.
High-Severity Alert Analysis
Key findings from the alert data.
  • Fraud Suspect alerts are critical with 10 open cases.
  • Late Payment and Low Balance are the most frequent high-severity alerts.
  • Over Limit alerts also contribute significantly to high-severity cases.
  • Repeat alerts are concentrated among a few customers.
Summary
Focus on Fraud Suspect and Late Payment alerts for risk mitigation.
Explore
03Visualize

Charts appear without the request.

Catalyst picks the right visualization for the question. Ranked counts become horizontal bars; time series become multi-line trends; category breakdowns become donuts. Every chart is interactive, downloadable, and ready to pin.
Open Alerts Count by Severity Level and Alert Type
Alert Type
1.0
18
2.0
15
3.0
10
4.0
10
5.0
9
6.0
9
7.0
8
05101520
Open Alerts Count
Monthly Customer Satisfaction Scores by Alert Type
5.04.03.53.02.5
2025-042025-052025-062025-072025-082025-092025-102025-11
Month
Dormant AccountFraud SuspectLarge TransactionLate PaymentLow BalanceOver LimitUnusual Activity
04Pin

Pin any card. Catalyst builds the dashboard.

Every answer and chart can be pinned. Catalyst arranges the pinned cards into a live dashboard with zero layout work, and each card stays tied to the query that created it — so the numbers refresh when the underlying data does.
Watch a team assemble a dashboard in one conversation
Dashboard
HNW Client Analysis
Add a description…
Cards Briefing
Repeat High-Severity Alerts by Customer
Evidence
  • Nikkel, Young & Jennifer each have 6 high-severity alerts
  • Rachel Brown + Michael Thompson follow with 5 alerts each
  • Top 4 customers account for the highest number of repeat alerts
Summary
Top customers have multiple high-severity alerts, indicating potential issues.
Top Customers with Most Repeat High-Severity Alerts
Nikkel
6
Young
6
Jennifer
6
Rachel
5
Michael
5
Christopher
4
High-Severity Alert Analysis
Observations
  • Fraud Suspect alerts are critical with 10 open cases
  • Late Payment and Low Balance are the most frequent
  • Over Limit alerts contribute significantly to severe cases
  • Repeat alerts are concentrated among a few customers
Summary
Focus on Fraud Suspect and Late Payment alerts for risk mitigation.
Monthly Customer Satisfaction Scores by Alert Type
05Brief

One click — executive briefing.

Click Briefingon any dashboard and Catalyst writes the narrative: an executive summary, the data highlights, the key findings, and the recommended actions — drawn from every pinned card. Board-ready in under a minute, re-generatable when the data changes.
See how this replaced a quarterly consulting deliverable
Dashboard
HNW Client Analysis
Cards Briefing
HNW Client Analysis
AI-Generated Executive Briefing
Executive Summary

The analysis highlights a significant number of repeat high-severity alerts among top customers, which correlates with fluctuating customer satisfaction scores across different alert types. Addressing these alerts is crucial to maintaining client satisfaction and trust.

Data Highlights
High severity alert count
Top customers with most alerts
Identifying these customers helps prioritize risk-management efforts.
Customer satisfaction scores
Fluctuations by alert type
Understanding these variations can guide improvements in customer service.
Fraud suspect alerts
Associated with lower satisfaction scores
Addressing fraud alerts is critical to maintaining customer trust.
Key Findings
  • Several top customers are experiencing repeat high-severity alerts, indicating potential systemic issues.
  • Customer satisfaction scores vary monthly, with notable dips associated with fraud suspect alerts.
  • Dormant account alerts have a less pronounced impact on customer satisfaction compared to other alert types.
Recommended Actions
  1. 1Investigate the root causes of repeat high-severity alerts for top customers to mitigate future occurrences.
  2. 2Enhance fraud detection and prevention measures to improve customer satisfaction scores.
  3. 3Develop targeted communication strategies for customers affected by large-transaction alerts to maintain trust.
Enterprise-ready conversational analytics

Catalyst doesn’t replace your warehouse. It makes it answer.

Plugs into your warehouse

Snowflake, Databricks, BigQuery, Postgres, MySQL, SQL Server. Point at your tables and start asking — no ETL, no new model required.

Bring your own LLM

OpenAI, Anthropic, Google, Groq, or a private deployment. Configure per tenant. Swap models without changing a line of your team's code.

Business language, not SQL

Operators ask in plain English. Catalyst maps vocabulary to schema, runs safe queries, and speaks back in headings, bullets, and charts.

Built for teams

Shared conversations, pinned dashboards, role-scoped use cases, capability-based permissions. Analysts set the rails; operators self-serve.

Enterprise-grade guardrails

Per-query SQL validation, schema-aware prompt injection defense, output schema enforcement, row-level access, tenant isolation.

Auditable by design

Every question, SQL query, model used, and card returned is logged and replayable. Legal, compliance, and audit teams can reconstruct any answer.

Try Catalyst on your data

Ask one real question. Get a real answer.
In the same meeting.

Send us a sample through a secure channel — or we’ll provide one. We’ll stand up Catalyst, connect a single warehouse, and answer your hardest business question live in the same working session. No procurement cycle required.

· Plug in any warehouse· Bring your own LLM· Answers in the working session