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Is this your company? Claim itWe offer continuous external attack surface monitoring and automated penetration testing, with human testers validating findings before clients see them.
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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 run a platform where brokers design and manage their own insurance products, so routine requests and policy changes keep piling up. We want AI helpers that handle the repetitive ones without adding headcount. A good solution must understand insurance regulation, plug into our policy system, keep humans in control of changes, and show clear pricing.
Telemetry from our many production clusters keeps growing faster than the budget we set for observability. We want to keep what matters for debugging while cutting noise and storage spend. A good solution must handle huge distributed fleets, offer clear, predictable pricing, let us choose how long data is kept, and keep all data inside our regions.
Our engineers across several countries lose hours chasing issues through chains of APIs, because each team owns its own dashboards and nobody sees one request end to end. We want tracing that builds on open telemetry standards, works on managed containers, handles many tenants at scale, and lets teams adopt it step by step without ripping out what they have.
We run machine learning models for pricing and member engagement, deployed as services by data engineers, and checks before release are left to each team. We want one disciplined evaluation routine that works alongside actuarial staff, keeps an audit trail of model decisions, and runs inside our own cloud tenancy. Insurance references matter.
We run managed clouds at many remote sites with engineers across time zones. Network and storage faults keep bouncing between shifts, and ownership gets lost at handoff. We need escalation that follows the shift, clear handoff notes, support for physical gear, and one view across many customer sites. Not a tool that assumes a single public cloud.
When a database or platform incident hits, our customers' payments stall, and we feel it immediately. Today our engineers lead live incidents with in-house alerting and scripts. We need earlier detection, clear on-call coordination across European and Asian time zones, and a full audit trail of every response step. It must fit our existing ticketing and cloud setup.
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 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?
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