Real work. Real results. Here's what we've built.
A media company needed to produce over 40 daily and weekly newsletters across multiple industry sectors — finance, legal, property, healthcare, education, and regional news — covering the UK, US, Asia-Pacific, and Australia. Each newsletter had different editorial requirements, source priorities, and audience expectations. Producing them manually required hours of journalist time every morning and was becoming unsustainable as the operation grew.
A fully automated content pipeline that collects news from hundreds of sources, uses AI to select the most relevant stories for each publication, writes professional editorial summaries, structures the content into the correct format, and delivers finished newsletters ready for review — all before the editorial team starts their day.
Each newsletter has its own configuration: which sources to prioritise, how to structure sections, what counts as a lead story, and rules to ensure quality and relevance. The system handles deduplication across publications so the same story doesn't appear in multiple newsletters, and it recovers automatically if a source goes down or returns fewer results than expected.
Newsletter production time dropped from several hours to under ten minutes of human review. The operation scaled from a handful of titles to over 40 without adding editorial headcount. New publications now launch in days rather than months.
A publishing business wanted to understand who was advertising in competitor newsletters and industry publications, so their sales team could approach those brands with data-backed pitches rather than cold calls.
An automated monitoring system that scans competitor newsletters daily, identifies sponsors and advertisers, enriches the data with company information and contact details, and feeds qualified leads directly into the sales team's CRM. The system tracks sponsor frequency, estimates spend levels, and flags when a new advertiser enters the market or an existing one increases activity.
The sales team went from guesswork and manual research to having a live, enriched pipeline of prospects — reaching brands at the moment they were actively investing in newsletter advertising, with specific data about their current spend and placement.
A growing services business was managing client onboarding across email, spreadsheets, and a project management platform, with no consistent process. Tasks were being missed, handoffs between team members were unclear, and new clients sometimes waited days for their first deliverable.
An end-to-end automation that triggers from the moment a new client signs up. It creates a project workspace, assigns tasks to the right team members, sends welcome emails, schedules kickoff meetings, and sets up recurring check-ins. Status updates flow automatically to the client, and the management team gets a live dashboard showing every active project's progress.
Client onboarding time was cut by more than half. Nothing falls through the cracks because the system tracks every step. The team can take on more clients without more admin overhead.
A business operating across multiple brands needed to manage email campaigns, audience segmentation, and performance reporting across several email marketing accounts. Each brand had different subscriber lists, sending schedules, and content requirements. Reporting was manual and time-consuming.
A centralised automation layer that manages campaign creation, audience segmentation, and scheduled sends across all accounts from a single control point. Automated reporting pulls open rates, click-through rates, and subscriber growth into a unified dashboard, broken down by brand, campaign type, and time period.
Campaign management time dropped significantly. The marketing team can now launch coordinated campaigns across all brands in minutes rather than hours, and performance data is available in real-time instead of compiled manually each week.
Every project above started with the same question: "Where are we spending human time on work a machine could do better?"
We didn't replace people. We freed them up to focus on the work that actually needs a human — editorial judgement, client relationships, creative strategy, and business decisions. The machines handle the repetitive, time-consuming, error-prone tasks that used to fill their days.
That's what good automation looks like. Not technology for its own sake — technology that gives people their time back.
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