Headless Wagtail
Wagtail as a content backend feeding Next.js, SvelteKit or native mobile. REST or GraphQL, preview mode, ISR, image renditions, and AI features sitting in the same domain model.
Our practice
Four practices, one team. We move in small, senior squads — usually one lead engineer plus a specialist. Everything we ship is production-ready Python: typed, tested, observable, and easy for your team to take over.
Editor-first publishing platforms in Wagtail — StreamFields, custom blocks, headless GraphQL/REST, multi-site, multi-language, and AI-assisted editorial tooling. We've been contributing to Wagtail since 2015.
Wagtail as a content backend feeding Next.js, SvelteKit or native mobile. REST or GraphQL, preview mode, ISR, image renditions, and AI features sitting in the same domain model.
One Wagtail install backing many public sites in many languages, with editorial workflow, translation review, and accessibility checks built into the publishing flow.
Block-based content modelling that gives editors flexibility without compromising your data model. Custom choosers, validators, block-level previews and rich admin panels.
Greenfield Django backends and rescue work for existing monoliths. We've shipped Django since 2012 — domain modelling, DRF / async APIs, background workers, multi-tenant patterns, and migration strategies that don't break production.
Typed models, sensible DRF, async views where they earn their keep, Celery for the rest. Clear domain boundaries, proper tests, infrastructure-as-code from day one.
9-year codebases brought back to life without big-bang rewrites. We untangle migrations, kill circular imports, add typed boundaries, and ship in small, safe steps.
Infra, CI/CD, evals in CI, prompt versioning, cost & quality dashboards, on-call runbooks. The unglamorous work that turns a clever prototype into a production system your team can sleep through the weekend on.
Versioned REST and GraphQL APIs, webhook architectures, third-party integrations, OpenAPI specs and developer docs that don't lie. We build APIs that outlive the project that asked for them.
Independent review of your existing Django or Wagtail platform — performance, security, architecture, editorial workflow, and a prioritised remediation plan you can actually execute against.
We treat LLMs as just another dependency — typed inputs and outputs, deterministic tests, evals on every PR, and a clear story for cost, latency and failure. The result is AI features your team can own, debug and improve.
pgvector or Pinecone, hybrid BM25 + dense, query rewriting, citation-grounded answers. Wired into your existing Wagtail or Django models — no parallel content store.
LangGraph-style state machines, tool calling against your real services, human-in-the-loop, structured streaming. Memory, recovery and observability baked in.
Offline eval suites, regression tests in CI, prompt versioning, PII redaction and red-team harnesses. Ship LLM changes with the same confidence as any other deploy.
Wagtail dashboards for content teams — drafts, tone-matching, translation, alt-text, SEO suggestions, asset tagging. Editors stay in control; the AI does the grunt work.
Llama, Mistral, Qwen and friends on your own GPUs or VPC. We handle vLLM, batching, quantisation and the security paperwork. Suitable for regulated and public-sector clients.