Work, with the numbers attached
Where a number was recorded before the work started, it is here with the number it moved to. Clients are named where they agreed to be named; the rest by descriptor and industry, because this work touches internal processes.
The method is the same throughout. A process is measured before anything is built, a system is built to remove it, and the result is reported against the number recorded at the start.
The stack varies more than the method does. What decides the shape of an engagement is the process, not the technology, and several of these ran across more than one of the four services.
33 in 100
Client-reported approximate figures: visitor questions that became booked consultations, in the first 2.5 weeks after launch
Client-reported: 100 questions to 33 consultations in 2.5 weeks
The client reported roughly 100 visitor questions in the first 2.5 weeks after launch, and about 33 of them became booked consultations.
a US law firm. Legal services.
- AI agents and LLM systems
- Data and backend engineering
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$77M
political TV ad spend tracked and attributed, an approximate total
Turning FCC filings into an estimated $77M of political ad spend
A four-stage LLM pipeline that turns raw FCC contract filings into queryable weekly ad spend, with every dollar traceable to its source document.
a US political advisory practice. Political intelligence and advertising.
- AI agents and LLM systems
- Data and backend engineering
- Workflow automation
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10×
cheaper monthly automation, from $500 to $50
From $500 to $50 a month: rebuilding an agency automation stack
Migrating a digital agency off a hosted no-code platform onto self-hosted n8n and Python cut costs 90% and responses from 3 minutes to under 20 seconds.
JIA NOMADS LIMITED. Digital agencies and product development.
- Workflow automation
- AI agents and LLM systems
- AI strategy
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under 2 minutes
to compile the weekly lead report, down from 5 hours
From 5 hours to under 2 minutes: a legal firm's lead report
Re-engineering a manual weekly lead report with n8n and AI-powered validation cut it from 5 hours to under 2 minutes for more than 12 executives.
a US legal services firm. Legal services.
- Workflow automation
- AI agents and LLM systems
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75%
fewer manager interruptions, by the client's own estimate
An estimated 75% fewer manager interruptions across 5 locations
A bilingual English and Spanish operations assistant answers 20+ daily staff questions about recipes and SOPs across a 5-location restaurant group.
Padrino's Cuban Cuisine. Hospitality, food and beverage.
- AI agents and LLM systems
- Workflow automation
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8
specialized assistants reachable from one Slack conversation
Eight AI assistants a creative agency talks to in Slack
A master agent reads requests arriving in Slack and delegates them across eight specialized assistants, so nobody routes the work by hand.
Crescendo Creative. Advertising and marketing.
- AI agents and LLM systems
- Workflow automation
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2 hours
runtime of a critical data process before the work
From 2 hours to 9 minutes: re-engineering an enterprise data process
Re-engineering the query layer of a critical data process cut its runtime from 2 hours to 9 minutes. Founder experience from a prior enterprise engagement.
a multi-billion dollar enterprise client. Enterprise software.
- Data and backend engineering
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<1 min
agent response time, down from minutes per response
From minutes to under a minute: a guest messaging RAG rebuild
Rebuilding an over-engineered retrieval layer from first principles, and moving ingestion off a monolith, cut AI guest replies from minutes to under a minute.
Cortado, Inc.. Property rental, real estate and travel.
- AI agents and LLM systems
- Data and backend engineering
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two
product iterations built: a messaging-first assistant, then an iOS MVP
From messaging prototype to iOS MVP: the backend behind Tomo AI
One agentic backend, with skills for task, email, and calendar workflows, carried a contextual AI assistant from a messaging prototype to a Flutter iOS MVP.
JIA NOMADS LIMITED. Digital agencies and product development.
- AI agents and LLM systems
- Data and backend engineering
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Your process is on this list in some form
The reading that costs a person a day a week, the report nobody wants to compile, the questions that interrupt the same manager. Tell us which one is yours and we will tell you whether it is worth automating.