AI Agent for Regulated Financial Data

Rivlo makes retrieving data effortless and instant, all while ensuring your data stays securely on-prem.

Data stays in your environment

macOS · Windows · Linux

Rivlo demo - Ask in plain English

“Show chargebacks by state for the last 30 days, highlight outliers”

-- Chargebacks by State (Last 30 Days)
WITH state_counts AS (
  SELECT state,
         COUNT(*) AS chargebacks,
         AVG(amount) AS avg_amount
  FROM   payments
  WHERE  status = 'chargeback'
    AND  created_at > NOW() - INTERVAL '30 days'
  GROUP BY state
),
overall AS (
  SELECT AVG(chargebacks) AS avg_cb
  FROM state_counts
)
SELECT s.state,
       s.chargebacks,
       s.avg_amount,
       CASE WHEN s.chargebacks > 2 * o.avg_cb
            THEN 'Outlier'
            ELSE '-'
       END AS flag
FROM state_counts s
CROSS JOIN overall o
ORDER BY s.chargebacks DESC;

Chargebacks flagged by state over the last month.

Results (last 30 days)

State	Chargebacks	Avg Amount	Flag
GA	128	$73.21	Outlier
AL	94	$68.02	Outlier
NC	42	$55.19	—

* Demo data; Rivlo never copies your source tables.

Connect Securely

Connect your database to Rivlo. Connections run inside your environment.

Ask in Plain English

AI helps draft SQL from your question using schema context - no row-level data leaves your environment.

Review & Run

Edit the SQL, run against your sources, and export results.

The Fastest Way to Your Data.

💬AI-Drafted SQL. Turn plain-english questions into SQL using schema context only.
🏠On-Prem Deployment. Rivlo runs locally, meaning data never leaves your environment.
🧠AI Tailored to You. Upload a file of commonly run SQL queries to train the AI on your business - it learns how your analysts think and speak.
🔌Connect Your Stack. Postgres, Snowflake, SQL Server, MySQL, Redshift, and BigQuery.
🗂️Query History. Save and reuse queries your team can read and trust.

Talk to Sales See the Architecture

“Which merchants had the highest total chargeback amounts last quarter?”

SELECT merchant_id,
       SUM(amount) AS total_chargebacks
FROM   payments
WHERE  status = 'chargeback'
  AND  created_at >= DATE_TRUNC('quarter', CURRENT_DATE - INTERVAL '1 quarter')
  AND  created_at < DATE_TRUNC('quarter', CURRENT_DATE)
GROUP BY merchant_id
ORDER BY total_chargebacks DESC
LIMIT 10;

A real-world financial investigation turned into SQL.

“Show daily revenue trends over the past month.”

SELECT DATE(created_at) AS day,
       SUM(amount) AS total_revenue
FROM   transactions
WHERE  created_at >= CURRENT_DATE - INTERVAL '30 days'
GROUP BY day
ORDER BY day;

Quick time-series revenue breakdown.

“Which states had the most refunds last month?”

SELECT state,
       COUNT(*) AS refund_count
FROM   payments
WHERE  status = 'refund'
  AND  created_at >= DATE_TRUNC('month', CURRENT_DATE - INTERVAL '1 month')
  AND  created_at < DATE_TRUNC('month', CURRENT_DATE)
GROUP BY state
ORDER BY refund_count DESC;

Refund patterns by geography.

Platforms

macOS · Windows · Linux

Distribute a desktop app; manage it with your normal tooling.

Seamless Database Connectivity

Rivlo works with your existing data stack - no migration needed.

PostgreSQL

Open Source

MySQL

Open Source

Snowflake

Cloud Data

Redshift

AWS

BigQuery

Google Cloud

SQL Server

Microsoft

Data Stays Put. Rivlo Comes To You.

Rivlo runs in your environment. The desktop client connects to your databases; queries execute against your systems. To help draft SQL, Rivlo calls OpenAI’s LLM with schema-only context (e.g., table and column names). No row-level data or query results are sent to OpenAI. You review and run the SQL locally.

• Direct connections you set up to your sources
• Schema metadata may be shared with OpenAI to generate SQL
• Results stay local; exports happen inside your perimeter

High-level flow

Your Environment (VPC / Colo)

Postgres

Snowflake

SQL Server

MySQL

BigQuery

Redshift

Rivlo Desktop Client

• Collects schema names to form prompts
• Calls OpenAI to draft SQL (no actual data sent)
• You review, run, and export locally

Security, Kept Simple

🔒Your Environment. Rivlo runs where you run; data stays in your network.
📄Schema-only to OpenAI. We share table/column names to help draft SQL - no database rows.
🧰Your Tools. Keep using the identity, logging, and deployment processes you already trust.

For highly-regulated data teams

• Keep analysis close to your systems
• Reduce ticket queues with self-serve questions
• Share readable SQL for review

Frequently Asked Questions

If you don’t see your answer, use the contact form and we’ll follow up.

Does any of our data leave our environment?

No actual data ever leaves your environment. Only schema context is sent to OpenAI's LLM to help draft SQL. See Security & Architecture for how AI drafts SQL using schema-only context.

Can we tune Rivlo to our business language?

Yes. You can upload a file of commonly run SQL queries. Rivlo uses the corpus to tailor suggestions to your terms and patterns.

Which platforms are supported?

macOS, Windows, and Linux desktop clients.

Get a Live Demo

Tell us a bit about you. We’ll tailor a walkthrough for your team.

• Ideal for teams that store highly-sensitive data
• Bring a sandbox schema or we’ll use demo data
• 30–45 minute session with Q&A