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Is this your company? Claim itWe build an ambient documentation assistant used by clinicians in many countries, and our engineering and go-to-market teams have grown quickly across several offices.
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Our agents guide employees on benefits and file claims, so a wrong answer has real consequences. Every model change needs a repeatable check that accuracy held. We need evaluation sets we own and control, step-level tracing of what the agent did, and clear regression reports before release. Must pass a security review and never train on our customer data.
When inference demand surges, our on-call engineers drown in manual steps. We need remediation that runs automatically from runbooks, understands custom hardware telemetry, and can be self-hosted on our own private infrastructure. Generic tools built for commodity servers fall short. Anyone else automating response across hardware and cloud layers?
We want AI coding help for our auditors, but the code we review belongs to clients and cannot leave our control. A good solution runs self-hosted or in a private deployment, never trains on our data, and has clear retention rules. Licensing must suit a small expert team, not large enterprise seat minimums. We are ready to trial now.
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 services across two regions, and when a security or production incident hits, the handoffs get messy. Who leads, who talks to regulators, and who owns the timeline is often unclear. We need a process and tooling that clarifies roles fast, keeps an auditable record, and works across both regions without slowing engineers.
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 wish for evaluation tooling built for regulated advice. It would score our model's explanations of portfolio decisions against clear criteria, flag unsupported claims, and route doubtful outputs to a human reviewer with an audit trail. We would judge it by how fast a small team can trial it, how well it catches errors staff review finds, and whether it never trains on our data.
Our telemetry from new sites and cloud services is outgrowing our observability budget. We're stitching logging, monitoring and alerting from basic parts, and costs climb faster than our visibility. A good solution must let us control data volume and retention, expose everything through APIs, and scale across new sites without repricing fights or long lock-in before proving value.
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