What our work changes in practice
Selected examples from sales, legal, software, and VC work.
Complaints stopped taking half the team’s day
The sales team spent hours on complaints and difficult client conversations. Responses were written from scratch, and quality depended on who picked up the ticket.
- →A complaint-response flow can pull in the ticket, context, and likely objections before anyone answers
- →Draft responses and argument sets help reps avoid starting from scratch on common situations
- →An AI assistant helps keep replies factual and avoid emotional drag in difficult conversations
Fewer escalations to management. Response time dropped from 45–60 minutes to 10–15 minutes.
Billing reports get drafted faster with AI
Lawyers spent expensive billable time writing hourly client reports. Service descriptions were inconsistent, hard to delegate, and rebuilt from scratch each time.
- →A repeatable report structure can turn meeting notes and activity logs into client-ready text
- →Standardized wording and level of detail make reports easier to delegate without rewriting
More hours billed to clients. Billing prep dropped from 60–90 minutes to 10–15 minutes.
AI usage is finally under control
Developers used dozens of AI tools, each person chose their own, and management had no visibility into data, active tools, or client use.
- →An audit can show which tools are in use, where client data goes, and which licenses duplicate each other
- →A smaller approved stack and clearer usage rules make everyday AI use easier to control
- →Client-work compliance can be built into the rules so the team knows what is allowed
Individual licenses across multiple tools were consolidated into selected team licenses, so people could share best practice and work from the same setup.
Due diligence moves faster
Analysts reviewed 100+ page due diligence reports filled with verbose AI content. Deal comparison was inconsistent, and key risks got lost in the noise.
- →A workflow can extract the key risks, facts, and open questions from long reports
- →Comparison criteria can be standardized so each deal is reviewed the same way
- →An AI assistant helps clean up AI slop in decks and keep the noise down
The team catches critical risks earlier. Deal review time fell by about 5x.
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