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Is this your company? Claim itWe are a university spinout building local-language large models, offering consulting-led deployments plus a no-code generative app builder for enterprises and municipalities, now inside a larger telecom group.
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Our merchant monitoring is still periodic and manual. Officers in a regional hub check controls against every rule change by hand, so drift between reviews goes unseen. We need continuous monitoring that flags changes across European regimes, plugs in through an API, keeps full audit logs, and helps analysts triage cases. No rigid on-prem suites.
We test our controls by hand: sample reviews, walkthroughs, office documents, once a year. By the time evidence is gathered, it is already stale. We want evidence collected continuously, mapped to the several regulatory frameworks we answer to, and pulled from our ticketing and cloud tooling. It must not need a dedicated admin or a generic checklist.
We wish for a tool that maps each user's country to its own data transfer and retention rules, then enforces them automatically across our chat and developer platform. We would judge it by how current its legal coverage is, whether it adds zero chat latency, and how clearly it explains each decision to our compliance team.
Before every model change reaches partners, we must prove our symptom assessment still performs against clinical cases. Today we lean on synthetic cases and automated metrics, which feels thin. A good solution gives versioned, reproducible evaluation sets, clinician-reviewed scoring, regression comparison between model versions, and fits our release pipeline and quality agreements.
We wish a tool existed that flags compliance risks at project kickoff and tracks them through delivery, instead of catching issues late. We would judge it by per-project workflow tracking, a full audit trail, and whether it fits government accreditation reviews. Named enterprise support matters too. Consumer-grade tools without audit logs are a non-starter for us.
We collect device telemetry from a very large consumer base, and new privacy rules now require us to prove consent and enforce retention. Today legal and security staff handle this by hand, without proper tooling. A good solution must track consent per device, automate deletion schedules, produce audit evidence, and come with a local implementation partner.
Larger customers keep asking whether we hold a formal security certification, and today we answer with hosting commitments and local-market assurances instead of a broad attestation. We need a way to prepare for an audit without drowning a small engineering team. A good solution must keep evidence collection mostly automatic and keep all data in European data centres.
We publish claims about how coding agents behave on messy, real-world code, and today we rerun our benchmarks by hand each time a new model ships. It eats research time and results drift. We need repeatable runs we can trigger per model release, with comparable scores over time, light enough for a small team and modest budget.
Our bank clients expect independent assurance on our controls, and every cycle we spend weeks chasing evidence across teams and systems. We need something that gathers proof continuously from our cloud environment and pipelines, maps it to control frameworks, and keeps an audit-ready trail. Light rollout, no on-premise installs, and priced for a small team.
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