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Don’t take our word for it. Try the demos yourself.

Built for the way small law and accounting firms run, on sample data: sound methods, checked numbers and findings in plain language.

Automation

A monthly report, checked before it is sent.

Sample brief

The Monthly Firm Brief

Goal: get paid faster and stop unbilled work slipping, with every partner briefed on the first working day.

On the first working day of each month, the job pulls the month's billing data, runs its checks, and prepares the partner brief. If a check fails, nothing is sent and a person is alerted. Its checks reconcile invoices against payments. The brief then compares every figure with a year earlier and flags overdue invoices, unbilled work, heavy deadline weeks and rates falling behind the market. An accounting practice gets the same brief with engagements in place of matters.

Read the October 2026 brief →
Latest
Oct 2026
Invoiced
$210,952 (+13% on Oct 2025)
Flagged
4 items worth a look

Written November 2, 2026 · market panel: BLS producer price indexes, retrieved from FRED

Want to see what this looks like with your numbers? Start with a Quick-Start Data & Automation Assessment, in two weeks.

Start with the assessment

Demos

Email, records, calendar, team. Connected.

An email arrives and AI reads it into a fixed form. From there, fixed rules take over: plain, written-down checks that compare each value with your records, update them, put any deadline on the calendar and tell the right person in the team channel. The AI never decides where anything goes. Try it on the business closest to yours.

Built for your firm, the same workflow runs on n8n, with records and the audit trail in Supabase and the checking logic in Python, all inside accounts you own.

Want to see what this looks like with your numbers? Start with a Quick-Start Data & Automation Assessment, in two weeks.

Start with the assessment

Works with data from

  • QuickBooks
  • Clio
  • Salesforce
  • Shopify
  • Gmail and Outlook
  • Slack and Teams

Built with

  • n8n
  • Supabase
  • Python
  • Tableau
  • Power BI
  • Streamlit

Clio and QuickBooks are trademarks of their owners. Rada AI Consulting is not affiliated with or endorsed by them.

Dashboards

Goal, data, dashboard, insight.

  • Screenshot of the Retail and E-commerce Intelligence dashboard.
    Proof of Concept

    Retail and E-commerce Intelligence

    Goal
    Grow profit by protecting the customers and products that carry the business, and putting marketing money where it returns the most.
    Data
    Online Retail II, UCI Machine Learning Repository. CC BY 4.0.
    Dashboard
    Six pages: executive summary, revenue and seasonality, products, customer segments, countries, and a full methodology. Filter by date and country; download any table as CSV.
    Insight
    4.4% of identified customers bring in half of all customer revenue, and 97% of it comes from people who bought more than once.

    Source: Chen, D. (2012). Online Retail II [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5CG6D

    Read the full case study →
  • Screenshot of the Workforce, Overtime and Retention dashboard.
    Proof of Concept

    Workforce, Overtime and Retention

    Goal
    Find out where overtime concentrates, who is at risk of leaving, and when it’s cheaper to hire than to keep paying time-and-a-half.
    Data
    Employee Compensation, DataSF (San Francisco Controller’s Office). PDDL (public domain).
    Dashboard
    Six pages: executive summary, pay structure, overtime risk, workforce movement, pay bands, and a full methodology. Filter by fiscal year, service area, department and job family; download any table as CSV.
    Insight
    Half of all overtime went to 5.2% of the staff, and the overtime bill grew 103% in nine years while base pay grew 61%.

    Source: City and County of San Francisco. Employee Compensation [Dataset]. DataSF. https://data.sf.gov/d/88g8-5mnd

    Read the full case study →

Want to see what this looks like with your numbers? Start with a Quick-Start Data & Automation Assessment, in two weeks.

Start with the assessment

Quick-Start Data & Automation Assessment

What the assessment hands you.

Proof of Concept

Sample assessment report

Goal: know in two weeks what your data can show today, and which fix to make first.

Three data sources and three workflows reviewed, the KPIs the data can support, the data-quality problems that get in the way, a ranked list of automation opportunities with estimated hours saved, a build-or-buy recommendation and three prioritized next steps.

Read the sample report →
  1. Review of up to 3 data sources and up to 3 current workflows or tools
  2. KPI and data-quality findings
  3. A ranked list of automation opportunities, with estimated hours saved
  4. A build-or-buy recommendation
  5. 3 prioritized next steps
  6. 60-minute walkthrough
  7. One round of written questions on the report

2 weeks · findings feed straight into any dashboard or automation build

Wondering what this would look like on your data?

A free call, no slides. Tell us what takes up the most hours in your week, and we will tell you honestly whether it can be fixed and what it would take.

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All examples use sample data: public datasets with their sources cited, or made-up firms. No client data, ever.