Services · AI Tooling

AI features that solve real problems.

LLM integration, RAG systems, document processing, semantic search, and AI-augmented internal tools — built for actual business value, not press releases.

+1 (206) 519-0882
(01) — Overview

AI Tooling & Integration, done right.

The AI hype cycle produced a lot of demos and very few production systems. We build the latter: AI features that quietly ship inside real products and pay for themselves in the first quarter.

Examples from client work: an intake triage system that classifies incoming legal matters by type and urgency, a document processing pipeline that extracts structured data from thousands of PDFs, a semantic search engine that lets clients find relevant matter history without exact keywords, and an internal Q&A system that answers ops questions from company documentation. All boring, all valuable, all shipping.

(02) — What we build

Scope of work.

LLM-powered chat and Q&A features
Retrieval-Augmented Generation (RAG) systems
Document processing pipelines (PDF, contracts, invoices)
Semantic search over internal knowledge bases
AI-augmented internal ops tools
Auto-summarisation and content generation flows
Custom AI agents with tool use
AI safety, guardrails, and evaluation harnesses
(03) — Tech stack

What we build with.

LLM Providers
  • OpenAI (GPT-4o, o1)
  • Anthropic (Claude)
  • Google (Gemini)
  • Open source (Llama, Mistral) via Together, Groq, Ollama
RAG / Search
  • Pinecone
  • Weaviate
  • pgvector
  • Elasticsearch
  • Meilisearch
  • Typesense
Frameworks
  • LangChain
  • LlamaIndex
  • Vercel AI SDK
  • Custom orchestration
Ops
  • LangSmith (evaluation)
  • Braintrust
  • Custom eval harnesses
  • Sentry (production monitoring)
(04) — Process

How we work.

01

Problem framing

Not every problem is an AI problem. First hour: figure out what you actually need. If it's not AI, we tell you.

02

Prototype + eval

Working prototype in weeks 1-2. Alongside: an evaluation harness that quantifies output quality — so we can measure improvements, not just ship vibes.

03

Production hardening

Guardrails, rate limits, cost monitoring, retry logic, fallback models, prompt versioning. AI in production has 10× more failure modes than a prototype.

04

Launch + iterate

Ship to a small user cohort first. Watch outputs. Tune prompts and retrieval. Then expand.

(06) — FAQ

Questions we hear often.

Depends on the problem. Great fits: classification, summarisation, semantic search, drafting, document processing. Poor fits: exact-accuracy tasks, low-latency real-time systems, high-stakes decisions without human-in-the-loop. We advise honestly.
Depends on your use case, latency needs, budget, and data sensitivity. OpenAI for general use. Anthropic (Claude) for long-context and instruction-following. Open source for cost or on-premise. Often a mix. We help you decide.
Structured prompt engineering with versioning, A/B testing, and evaluation harnesses that quantify improvement. We don't "vibe check" prompts to production — every change is measured against a test set.
Every AI feature ships with cost monitoring, per-user quotas, cheap-model fallback for common cases, and caching where safe. AI costs get out of hand only when nobody's watching — we make sure someone is.
Yes. Tool-using agents with defined action spaces, guardrails, and human-in-the-loop approval where appropriate. Not autonomy for the sake of it — agents that solve a specific business problem better than a fixed workflow.
Ready to start

Let's talk about your project.

Every consultation includes a free custom concept for your project — no cost, no obligation. Book a 30-minute call at a time that works for you.

+1 (206) 519-0882
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