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Artem Frolov

Applied AI engineer & data scientist. London.

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I build AI systems for real workflows. I’m a Senior Data Scientist at Domestic & General, working on Generative AI solutions and machine learning in insurance.

My work spans the business case, architecture and implementation through to evaluation, governance and rollout. I care about systems people can inspect, challenge and use in their day-to-day work.

Outside work, I build mobile apps, explore on-device ML and run a Raspberry Pi homelab. This is a collection of my work, writing and experiments.

Case Studies

  • Complaints Sidekick

    Designing, evaluating and piloting an AI assistant that prepares complaint evidence for human review. An operational pilot showed roughly 20% higher throughput, with quality monitored alongside productivity.

    Business case, architecture, implementation and stakeholder engagement.

    Databricks · LangGraph · MLflow

  • Customer Call Transcript Analysis

    A daily Databricks workflow that turns customer call transcripts into structured data for teams to investigate recurring issues and sentiment.

    Daily batch pipeline, structured LLM extraction and an app for Operations.

    Databricks · Unity Catalog · Python · OpenAI Batch API

Experience

Domestic & General

Aug 2023 — Present

Senior Data Scientist, AI · London, UK

Building AI assistants, machine learning models, and pricing tools in a regulated insurance business. Leading work from business case and architecture through evaluation, governance, and rollout.

  • Led Complaints Sidekick from business case and architecture to Production, with complaint handlers reviewing AI summaries, evidence, and recommendations.
  • Built evaluation, monitoring, and feedback frameworks with usage logs, traceable outputs, quality assurance review, and human oversight.
  • Delivered AI assistants for pricing and analytics teams to investigate model performance and verify deployments, reducing manual analysis effort by approximately 80%.
More responsibilities & contributions
  • Introduced CI/CD, automated testing, model versioning, and reproducible training pipelines, reducing deployment timelines from approximately one month to under one week.
  • Developed the organisation's first production cancellation propensity model for pricing decisions, with an approximately 4% improvement in first-year customer retention.
  • Delivered pricing optimisation using Earnix, simulations, elasticity modelling, and lifetime value analysis.
  • Worked with senior stakeholders across Pricing, Decision Science, Complaints, Operations, Risk, and Assurance to define requirements and deliver governed systems.

Paloma Labs

Nov 2025 — Present

Co-Founder / Builder · Delaware, US

Building analytics and machine learning tools for mobile apps, with a focus on event tracking, on-device prediction, and developer experience.

Selected contributions
  • Built early Swift SDK prototypes for automatic and manual event tracking.
  • Designed event ingestion, session processing, and analytics schemas with FastAPI, PostgreSQL, and Redis.
  • Explored on-device inference for behaviour prediction and privacy-conscious product analytics.
  • Built web tools for configuration and analytics exploration.

Blog

All blog posts

Experiments

  • AIrcade

    In-browser games and interactive experiences. Start with a journey from Earth to the cosmic web.

  • Model Creativity

    One prompt, different models. An ongoing collection of creative experiments, starting with Astra.

All Experiments

Tools & focus

Applied AI, agentic workflows, retrieval, evaluation and production ML. I work across the model, the application and the infrastructure around it.

Tools I work with
Languages & Data
  • Python
  • SQL
  • Spark
  • TypeScript
  • Swift
  • Power BI
AI & ML
  • OpenAI API
  • Databricks
  • MLflow
  • LangGraph
  • LangChain
  • Scikit-Learn
Web & Backend
  • FastAPI
  • PostgreSQL
  • React
  • Next.js
  • Tailwind CSS
Infra & Tools
  • Docker
  • Nginx
  • Cloudflare
  • Tailscale
  • Git

Background

Durham University

BEng, Electronics Engineering
Sep 2019 — Jun 2022

Studied electronics, communications, signal processing, control systems, mathematics, and applied statistics, with practical work in modelling and engineering design.

University project work
  • Led a six-person project on the engineering and commercial feasibility of torsion bar suspension for armoured vehicles; the project received a first-class mark.
  • Applied mathematical modelling and control theory to evaluate system performance and engineering trade-offs.

Certifications

Elsewhere

Open to conversations about applied AI, AI products, infrastructure and agentic systems.

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