Why one LLM isn't enough: routing prompts across models without losing control
Model quality changes every month. Here's how we design routing, fallbacks and cost caps so your product never depends on a single AI vendor.
Running one website is a job. Running dozens with a small team is only possible if the repetitive work is automated. Over the past few years we've built a set of backend tools for exactly this — first for our own publishing operation, then for clients facing the same problem.
One analytics view for every site
Logging into a separate dashboard for each site wastes the most valuable hour of the morning. We built an aggregation service that pulls realtime visitors and 24-hour trends from every site into one grid, adds uptime checks, and even shows the key numbers in a browser extension.
Publish once, distribute everywhere
Copy-pasting the same story into site after site is slow and error-prone. Our AI-assisted publishing engine takes one article, produces a distinct version for each site, and publishes to whole groups of sites in parallel — with live progress for every job and a full history.
Know what's indexed
A page that isn't indexed doesn't exist as far as search is concerned. A bulk index monitor checks thousands of URLs per run, rotates API keys to stay within quotas and streams progress live, so SEO teams can audit at scale.
Learn from the past
When evaluating domains or planning content, it helps to know what a site used to publish. An archive recovery engine indexes historical snapshots, previews old pages and exports the data for analysis.
Keep the team organised
Finally, simple internal tools — a link organiser, a daily work tracker, a publishing overview — replace the spreadsheets and chat threads that small teams usually run on.
The pattern
None of these tools is huge. Each one removes a specific, repeated task. Together, they let a small team operate at a scale that would otherwise need many more people. See the full stories in our portfolio, or tell us about your workflow.
