We run capacity across many data centers in several countries, and our compliance work cannot keep pace with our growth. Mapping several frameworks by hand is slow. A good solution must fit physical sites, not only cloud SaaS, automate evidence and framework mapping through APIs, roll out fast, and avoid heavy consulting. Audits are coming this year.
Healthtech · Life Sciences Software · 200–1000 · Europe #b034_10
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We sell risk-based monitoring and clinical data review software that helps trial sponsors spot data issues and site risks early.
- Industry
- Healthtech · Life Sciences Software
- Size
- 200–1000 employees
- Region
- Europe
- Tools budget
- $5K–20K per month
- Needs
- Regulatory reporting. Updated good clinical practice guidance raises expectations, and sponsors want inspection-ready reports straight from our platform.Today: statisticians prepare regulator-facing reports with manual checks against guideline updates · Urgency: this yearLLM evaluation & testing. Our machine learning coding and query features must show consistent precision across studies before customers trust them in regulated work.Today: product teams test new medical review models with a partner pharma before release · Urgency: this yearSOC 2 / ISO 27001 automation. Sponsor and CRO security reviews are frequent, and keeping our assurance materials current is a recurring scramble.Today: a trust centre maintained by quality staff with manual audit evidence · Urgency: this year
- Who decides
- head of product · security review
- Expects from suppliers
- Experience with validated models in regulated clinical settings; Exportable evidence suitable for inspectors; Supports both EU and US hosting
- Not a fit
- Model monitoring tools unaware of clinical trial data; Vendors without validation documentation
- Stack
- cloud: AWS-class hyperscaler, compliance tooling in place, ticketing / issue tracker
- Buying triggers
- regulatory change, AI adoption push
Needs
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Large enterprise buyers expect a current security attestation, and refreshing it every year still eats far too much of our small team's time during rapid migration demand. A good solution must collect evidence automatically across more than one public cloud, stay affordable at our size, and avoid pulling engineers off product work. Trial first, please.
We run several certifications across multiple legal entities, and every year the same control testing and evidence gathering gets repeated per entity. A good solution must map one control set across entities, reuse evidence across frameworks, keep scopes separate, support local data residency, and plug into our identity provider and ticketing.
Every new customer means our analysts read long plan documents and re-key benefit details into structured data by hand. It slows onboarding and invites mistakes. A good solution must pull values from insurance plan summaries, flag low-confidence fields for human review, and validate against known plan rules. Plain OCR does not help us.
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 hold deeply sensitive personal health details, so consent and access controls must be airtight. Today privacy duties sit inside the same system as our certification, which feels thin. A good solution must track consent clearly, limit who sees what, log access, and stay light enough for a lean team to run without a dedicated security engineer.
Keeping our security certification current while answering partner questionnaires by hand is swallowing most of our compliance capacity. An audit is coming this year. A good solution prefills standard questionnaire answers, tracks evidence continuously across multi-region, hardware-heavy operations, and keeps pricing flat as we grow. Usage-based pricing tied to data volume is a dealbreaker.
We wish a tool existed that maps consent terms and cross-border transfer rules to each study, then flags conflicts before data moves. We would judge it by whether it supports per-study configuration, produces reports our regulators and reviewers can read, signs data processing terms, and keeps tamper-proof logs. Anything that cannot show its audit trail fails our security review immediately.
We wish for an evaluation workbench that reruns every model version against our full set of clinical findings and gives identical results each time, with locked data, code and settings. We would judge it by reproducibility across reruns, clear per-finding regression reports, audit trails fit for medical device reviewers, and how easily it plugs into our existing pipelines.
We wish for one place that keeps controls and evidence current across every framework we claim, with crosswalks between healthcare, payment and secure development requirements. We would judge it by how little manual evidence chasing remains before an audit, whether pricing is published upfront, and whether it fits a small budget and our existing pipeline.
Our claims and fraud handlers keep repeating the same manual lookups across systems, which eats time better spent on judgement. We want agents that automate those lookups safely, with clear audit trails, human approval on sensitive actions, and tight access controls. Insurance experience matters. Who has handled this well in regulated claims environments?
We run online consultations and pharmacy delivery, and new electronic invoicing rules mean every single order must reach the tax authority with accurate transaction data. Today that is manual and error-prone. A good solution must automate submission per order, flag rejected records for quick fixes, and stay light enough for a small team without dedicated engineers.