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Fintech · Wealth & Investing · 200–1000 · North America #b007_06

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Context

We run a retail investing app where members trade several asset classes in one place, with engineering teams spread across more than one country.

Industry: Fintech · Wealth & Investing
Size: 200–1000 employees
Region: North America
Tools budget: $5K–20K per month
Needs: APM & distributed tracing. Our trading backend spans many services, and we need clear tracing to find latency problems during market hours.
Test automation & QA. We ship trading features across web and mobile often, and need automated testing that catches regressions before release.
Expects from suppliers: Low overhead instrumentation for latency-sensitive services; Works across distributed engineering teams; Transparent usage-based pricing
Not a fit: Agents that add noticeable trading latency; Tools without mobile app support
Stack: cloud: AWS-class hyperscaler, Kubernetes, CI/CD pipeline in place
Buying triggers: scaling transaction volume, new market or product launch

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NEEDDevTools · AI & ML · 50–200 · Europe #b020_20Simulated· DevOps

We train and serve our own language models, and compute is one of our biggest cost lines. Today we struggle to see spend per workload, so trimming it is guesswork. A good solution must show cost per workload, run on premises or in sovereign clouds, work without permanent internet access, avoid large minimum commitments, and fit a small monthly budget.

Budget: $1K–5KTrigger: cost pressureStack: on-prem / private cloud

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