Georgie · AI implementation & automation

I help companies
put AI to work.

I partner with teams to design and build AI into their operations — from the first use case to systems running in production. I work with my clients on bespoke use cases, because every business is different and AI needs to be tailored to you.

G
georgieavailable

About

Hi, I'm Georgie.

I work with companies to bring AI into how they actually operate — finding where it creates real leverage, then designing, building and embedding it into their day-to-day workflows.

I go deeper than slide decks: I ship. From autonomous pipelines and fine-tuned models to the data layer underneath, I turn AI from a buzzword into systems teams can rely on.

Based in the UK. I partner with teams who want to move faster with AI — embedded as a builder, not just an advisor.

AI implementationAutomationApplied LLMsData systems

Services

Ways I help teams ship AI.

Whether you're starting from a blank page or scaling something that already works, I plug in as a builder across the full path — from finding the use case to running it in production.

01

AI strategy & discovery

I map where AI actually moves the needle in your business and turn it into a prioritised, no-hype roadmap you can act on.

02

Build & integration

I design and ship AI into your existing tools and workflows — production systems your team can rely on, not demos that die in a sandbox.

03

Agents & automation

Autonomous, multi-step workflows that take real work off your team's plate and run end to end — observable every step of the way.

04

Models & data

Fine-tuned models and the clean, enriched data layer underneath them, so the AI is accurate and trustworthy for your domain.

Flagship case study · AI recruiting platform

One brief in. A contacted shortlist out.

My deepest build to date — an autonomous recruiting platform — is a good window into how I work. It replaces the manual sourcing grind with a loop where autonomous agents work together, so recruiters spend their time on conversations, not spreadsheets.

01

AI Sourcing Pipeline

A fleet of autonomous agents runs five sourcing strategies in parallel across LinkedIn Recruiter, search intelligence and your talent pool — orchestrated, deduped and enriched into a single longlist from one role brief.

Multi-agentSemantic searchDedup engine
02

Intelligent Ranking

Every candidate is scored against the brief and your historical calibration. A self-improving model learns what a great hire looks like for each client and surfaces the strongest fits first.

CalibrationEmbeddingsSelf-improving
03

Outreach Automation

Agentic outreach drafts personalised InMail and connection requests, paced to platform limits and written in your voice. Replies flow back into the loop so nothing slips through the cracks.

AgenticRate-awareReply tracking
04

Database Building

A purpose-built data layer underneath it all — agents continuously ingest, dedupe and vectorise every record into a RAG-ready knowledge base the whole system can reason over in real time.

Vector storeRAG-readyAuto-enrichment

Case study · Features

The rest of the toolkit.

Beyond sourcing, ranking and outreach, the platform handles the unglamorous-but-critical parts of a recruiting desk — qualifying, formatting, scheduling and staying in sync.

CQ
Screening

Candidate qualifier

Screens every candidate against the live brief — scoring fit and flagging the strongest before a human ever opens the thread.

SG
Auto-format

Submission generator

Turns a shortlisted candidate into a polished, client-ready submission in seconds — formatted, summarised and on-brand.

BP
Self-serve

Booking page

A branded scheduling page synced to your calendar — no back-and-forth. Every booking drops the candidate straight into the database, deduped and enriched, so the people you meet are captured automatically.

TP
Dedup

Talent pool & dedup

Every candidate collapsed into one canonical record and kept warm, so the next role starts with a head start, not a blank page.

CL
Learning loop

Calibration & learning

Learns what a great hire looks like for each client from real outcomes, so every run is sharper than the last.

AS
Integrated

ATS sync

Pushes shortlisted candidates and stage changes straight into your ATS, so the platform and your system of record never drift.

Case study · Impact

The numbers behind the loop.

What autonomy actually buys a recruiting team — measured across live client pipelines.

0%
Less manual sourcing

Days of manual searching collapse into a single autonomous run.

0×
Faster to first shortlist

Brief to a ranked, contacted longlist in a day — not a week.

0+
Profiles screened per run

Surfaced, deduped and scored with zero manual screening.

0%
Lower enrichment cost

Expensive data is only pulled when it changes the outcome.

Projects

Built and running in production.

OS

AI Recruiting OS

Recruiting platform

An autonomous sourcing engine — five-strategy pipeline, semantic candidate matching, calibrated ranking and outreach, all wired into a single operating system for the desk.

  • End-to-end sourcing pipeline
  • Calibrated AI ranking
  • Outreach + reply tracking
AI

AI Ops Assistant

Conversational agent

A conversational layer over the entire recruiting stack — query candidates, trigger sourcing runs, draft outreach and pull pipeline status through natural language.

  • Natural-language control
  • Live pipeline queries
  • Action-taking agent
AD

Agent Desk

Multi-agent workflow dashboard

A dashboard for orchestrating multi-agent workflows with live canvas rendering — it plans, spawns parallel agents, routes tasks between them and streams every step to a live graph as it runs.

Real-time
agent-desk · live
LIVE
planOrchestrator decomposed goal into 6 subtasks
AGENTS
6 active
TASKS
24
LATENCY
0.41s
STATUS
RUNNING

Case study · Models

Recruitment chatbots, fine-tuned for the desk.

Off-the-shelf models don't understand your roles, your market or your voice. I fine-tune purpose-built models for each stage of the funnel — so the conversation feels like your best recruiter, at scale.

DATAFINE-TUNEDEPLOY
01

Screening

Qualifies in seconds

A model fine-tuned to qualify inbound candidates against a live brief — asking the right follow-ups and flagging the strongest fits before a human ever opens the thread.

02

Intake

Brief from a chat

Turns a messy hiring-manager conversation into a structured brief — must-haves, nice-to-haves, comp and calibration — so every downstream run starts from clean signal.

03

Outreach

Reply-optimised

Writes in your firm's voice across InMail, email and connection notes — trained on what actually gets replies, tuned per role and per market.

Case study · Data & enrichment

Turning sparse data into a searchable asset.

The hardest part of an AI recruiting system isn't the model — it's the data underneath it. Building it taught me how to clean, enrich and index people data so the rest of the pipeline can trust it.

01
Ingest
Pull from every source
02
Resolve
Dedup to one identity
03
Enrich
Fill the gaps, cheaply
04
Embed
Vectorise for meaning
05
Serve
Query in milliseconds

Identity resolution & dedup

Dedup engine

Collapsing the same candidate across five sources into a single canonical record — fuzzy matching on name, history and profile signals so the database never double-counts a person.

Cost-aware enrichment

~95% cheaper

Conditional profile extraction that only pulls expensive third-party data when it actually changes the outcome — the same approach cut enrichment spend by ~95% without losing coverage.

Semantic & vector search

pgvector

pgvector embeddings and similarity matching so a role brief finds people by meaning, not just keywords — backed by tuned RPCs that return ranked matches fast.

Schema & query performance

Postgres

Postgres schema design, row-level security, materialised views and indexes built to keep candidate matching quick as the dataset grows into the millions.

Get started

Let's put AI to work in your business.

Pick a time and tell me a little about what you're working on. You'll get a Google Meet invite the moment you book.

Prefer email? grobe009@gmail.com

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