ML Productionisation · LLM Integration · Predictive Analytics · AI Governance · Fractional CAIO
Valinor AI delivers production-grade machine learning systems, LLM integrations, and AI leadership for growth-stage businesses. We take projects from raw data to deployed, monitored systems — end to end.
Clients include
Seven practice areas, each grounded in production delivery.
MCP server design, RAG pipeline architecture, agentic workflow development, and LLM integration into existing SaaS stacks — CRM, ticketing, reporting, and beyond.
End-to-end lifecycle management from data ingestion through feature store, training, evaluation, serving, and monitoring. We turn prototype notebooks into CI/CD-integrated, observable pipelines.
Supervised fine-tuning on proprietary corpora — product catalogues, moderation datasets, customer service logs. Parameter-efficient approaches for constrained compute budgets.
Purchase likelihood, multi-touch attribution, churn prediction, CLV modelling, and lead scoring — delivered as CRM-consumable score outputs, built on transactional and clickstream data.
Scalable ingestion pipelines on GA4/BigQuery, Databricks Delta Lake, and dbt semantic layer — the governed data infrastructure that every AI system depends on.
Risk classification of existing AI/ML systems, EU AI Act conformity support, bias auditing, explainable AI methods, and board-ready technical documentation.
Senior AI leadership on a retained, part-time basis — AI strategy, vendor evaluation, team upskilling, board reporting, and delivery oversight. Right-sized for companies establishing their first AI function.
A selection of verified results — framed in revenue, cost, and risk terms.
Additional ad revenue generated by a sale-probability model identifying optimal inventory for third-party advertising — at 2.66× ROI, with a 4× increase in eligible inventory.
Real-time price forecasting model surfacing estimated sale prices at listing time, increasing completed listing rate and total gross merchandise value.
Purchase likelihood classifier triggering targeted CRM notifications. New user return rate doubled; early churn reduced by 5%.
Retrained product embedding model for interaction-based recommendations, reducing inference runtime by 20% — directly lowering serving cost at scale.
Feature engineering improvements to an existing fraud detection classifier — a 23% lift in PR-AUC before model retraining — then deployed to production.
Bayesian experimentation across acquisition touchpoints drove a 15% increase in ad click rate and 5% subscriber growth, followed by an epsilon-greedy bandit removing manual A/B scheduling.
Causal survey design demonstrating 17% incremental brand equity impact — a board-level measurement framework, not correlation analysis.
Demand prediction model across 1,000+ products enabling price point optimisation; extended to a reinforcement learning approach for continuous improvement.
Concrete deliverables with defined scope — designed for teams that need AI capability without a drawn-out discovery process.
Structured assessment of your data infrastructure, tooling, workflows, and AI capability. Output: a prioritised roadmap with commercial impact estimates. A natural starting point before committing to a larger engagement.
Connect your database or REST API to your AI assistant via the Model Context Protocol. Includes authentication, read-only query tools, schema documentation, and safety guardrails.
A retrieval-augmented generation pipeline over your internal documentation — Notion, Confluence, PDFs, SharePoint. Staff can query policies, procedures, and product specs in natural language.
Scheduled pipeline pulling from GA4, Sheets, SQL, or APIs — LLM-summarised and delivered via email or Slack. Replaces manually assembled reports with zero ongoing maintenance overhead.
A classifier trained on your CRM or product usage data, delivering a daily score column directly into the BI dashboard or spreadsheet your team already uses.
LLM integrated into existing business workflows — email triage, support ticket classification, document data extraction. High-value automation with a tightly scoped delivery.
Audit and remediation of ungoverned BI environments, particularly post-platform migration. Rationalises metric definitions through a dbt semantic layer to establish a single source of truth.
Valinor AI is a UK-based applied AI consultancy. We exist because the gap between what AI can do and what organisations actually ship is still enormous — and the gap is rarely a technical one.
We combine deep research-grade methodology with a commercial-first delivery mindset, working directly with the teams closest to the problem — from individual contributors to boards.
Based in London. Operating remotely across the UK and Europe.
We apply the same standards of evidence to commercial AI that we would to published research — reproducible, validated, and honest about uncertainty.
Academic rigour does not mean slow. We ship working systems — the simplest model that solves the business problem is always preferred over an unnecessarily complex one.
We own the outcome, not just the deliverable. Engagements are scoped around business impact, and we measure ourselves by the same metrics our clients use.
From data ingestion to monitored inference — we do not hand off mid-project. One accountable point of contact throughout.
A lean, transparent process with direct access to the practitioners doing the work.
A focused conversation about your business problem, data landscape, and current blockers. No obligation. We'll tell you clearly whether we're the right fit — and if not, point you toward someone who is.
A clear proposal — fixed-scope or time-and-materials — with defined deliverables and milestones. Typically turned around within 48 hours of the discovery call.
Regular updates throughout. Full visibility — no black-box development. We can engage via outside-IR35 contract or standard B2B consulting agreement, depending on your procurement requirements.
Clean documentation and structured knowledge transfer at project close. We build for your team to own and operate — not for ongoing dependency.
If your question isn't here, the discovery call is the right place to ask it.
Start with a 30-minute discovery call — no obligation, no sales process. We'll tell you exactly whether and how we can help.
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