GDPR-Compliant On-Device AI for European Insurance Mobile Apps in 2026 (Fixed-Price, Money-Back)

Your GDPR officer rejected the AI claims triage feature because the inference API sends policyholder data to a US-based LLM provider. Your claims team is still triaging manually.

Every day of manual triage is a day your claims team spends on work a model could handle in seconds. The compliance block is real, but it's solvable with the right architecture - one your GDPR officer can sign off on because the data never leaves the EU or the device.

The Project Shape

Four decisions determine whether this project ships in 6 weeks or circles through legal review for a year.

AI task scoping. Claims photo damage assessment, policy document summarization, and first-notice-of-loss triage have different model requirements. A multimodal model that assesses photo damage is a different build from a text model that summarizes policy documents. Building for all three in one sprint produces none of them well. Starting with the task that handles your highest claim volume - and delivers the clearest time saving to your claims team - means you have a result that justifies the next sprint.

On-device vs on-premise. If the policyholder's device runs the model, there is no data transfer at all. Your GDPR officer's objection evaporates structurally. If your EU-based servers run the model, there is no third-country transfer, but you retain a data controller obligation and need a DPA with whoever operates the infrastructure. The compliance path for on-device is shorter. The performance ceiling for on-device is lower. Your DPO and your engineering team both need to be in the room when this decision is made.

Special category data. Health and disability claims involve Article 9 data. The lawful basis for processing that data with AI is a separate legal question from standard claims data. "Legitimate interest" won't cover it. Your legal team needs to confirm the processing basis - medical diagnosis, social security, or vital interests - before any AI feature touches health claims data.

Model update cadence. An on-device model is a software artifact that needs to be updated when your claims policy changes or when the model's performance degrades on new input distributions. The mechanism for pushing model updates to policyholder devices has to be designed before you ship the first version, not figured out when you need to push the first update.

Most teams spend 4-6 months discovering these decisions by building the wrong version first. A team that has shipped this before compresses that to 1 week.

The Off Grid Anchor

We built Off Grid because we hit every one of these problems in production. Off Grid is the fastest-growing on-device AI application in the world, with 50,000+ users running it today. It's open source, with 1,650+ stars on GitHub and contributors from across the world. It has been cited in peer-reviewed clinical research on offline mobile edge AI. Every decision named above - model choice, platform, server boundary, compliance posture - we have made before, at scale, for real deployments.

The Delivery Shape

The engagement is four sprints. Each sprint is fixed-price. Each sprint has a named deliverable your team can put on a roadmap.

Discovery (Week 1, $5K): We resolve the four decisions - model, platform, server boundary, compliance posture. Deliverable: a 1-page architecture doc your CTO can take to the board and your Privacy Officer can take to Legal.

Integration (Weeks 2-3, $5K-$10K): We ship the on-device model into your app behind a feature flag. Deliverable: a working build your QA team can test against real workflows.

Optimization (Weeks 4-5, $5K-$10K): We hit the performance and compliance targets from the discovery doc. Deliverable: benchmarks signed off by your team.

Production hardening (Week 6, $5K): Edge cases, OS version coverage, app store and compliance review readiness. Deliverable: shippable build.

4-6 weeks total. $20K-$30K total. Money back if we don't hit the benchmarks. We have not had to refund.

"Wednesday Solutions' team is very methodical in their approach. They have a unique style of working. They score very well in terms of the scalability, stability, and security of what they build." - Sachin Gaikwad, Founder & CEO, Buildd

The Close

Worth 30 minutes? We'll walk you through what your version of the four decisions looks like, what a realistic scope and timeline would be for your app, and what your compliance posture and on-device target mean in practice. You'll leave with enough to run a planning meeting next week. No pitch deck. If we're not the right team, we'll tell you who is.

Book a call with the Wednesday team