RankStudio

What we do for clients.

Six practice areas, all delivered by senior consultants. We pick up work where the team is small, the brief is open, and the bar is high.

AI engineering and prototyping

We build evaluation harnesses, prompt libraries, and reference implementations. We pair with internal teams during their first production rollout, and we instrument what we ship so the next iteration is informed by data, not guesswork.

  • Eval harness for a customer-facing assistant
  • Prompt and tool-use library shared across three product teams
  • Reference RAG implementation, including ingestion and retrieval tuning
  • Latency and cost tracking for a multi-model pipeline

LLM-based application development

Full-stack work on AI-native products. Next.js, TypeScript, edge deploys, and the relevant model SDKs. We take a problem from a sketch to a deployed first version, then hand off cleanly or stay on for iteration.

  • Internal copilots that wrap proprietary data sources
  • Document review and extraction tools
  • Chat surfaces with retrieval and tool calling
  • Voice and transcription pipelines

Research and discovery

Structured discovery interviews, prior-art reviews, and vendor landscapes. We deliver a written report with sources, not a slide deck. Clients use the output to make a decision; if a decision needs a second round, we run it.

  • Use case scoring across a portfolio of 20 to 40 candidates
  • Stakeholder interviews synthesised into a single brief
  • Vendor shortlists with annotated trade-offs
  • Prior-art reviews citing primary sources

Technical writing and documentation

Reference docs, runbooks, and external technical content. The writers on the team have shipped product. They read the code and talk to the engineers before they write.

  • API reference and onboarding guides
  • Internal handbooks for AI teams
  • Technical blog posts under client byline
  • Public model and product changelogs

Vendor and landscape analysis

Independent comparisons of model providers, evaluation tools, frameworks, and infrastructure. No vendor relationships, no resale margin, no incentive to recommend the loudest option.

  • Foundation model side-by-side on a client task
  • Framework selection for a new product
  • Observability and eval tool comparison
  • Inference and hosting cost modelling

Workshop and training delivery

Working sessions for technical teams. We bring the curriculum, the exercises, and the model access. Sessions are small, hands-on, and tied to a real client codebase or dataset.

  • Two-day workshop for a platform engineering group
  • Hands-on prompt and eval workshop for product managers
  • Internal lunch-and-learn series on agentic patterns
  • Bespoke training tied to a specific deployment

How an engagement runs

Three short steps. Written scope, named consultant, fixed cadence.

01

Brief

A 45-minute call and a one-page written scope. No proposal theatre.

02

Build

A senior consultant runs the work. Updates are written, weekly, in your channel of choice.

03

Hand off

Deliverable, source, and a short loom walkthrough. Stay on for iteration if it makes sense.

Have a project in mind?

Tell us about it. One short form. We reply within two business days.

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