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THE BLUE BOX @TheBlueBoxDev
Joined April 2023
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Healthcare AI spending hit $1.4B in 2025. More than half of U.S. health systems are deploying ahead of formal regulation. HIPAA has no provisions for model drift, bias monitoring, or real-time observability. Compliance is a floor, not a safety guarantee.
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Deloitte: 1 in 3 generative AI users encountered incorrect outputs in 2025. In regulated industries, test accuracy is not the right metric. Calibration, confidence drift, and escalation rate are what production AI performance looks like.
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Relativity filed for IPO in March 2026, the first legal tech public offering since 2021. E-discovery is a data engineering problem at scale. AI is how litigation teams process terabytes of ESI in hours instead of months.
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Accenture 2026: AI-first credit systems increase automated approvals 50%, decisioning throughput 70-90%. Every credit denial requires an ECOA adverse action reason code. AI that approves in milliseconds but cannot explain denials is a regulatory liability.
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Payment fraud losses exceeded $48B in 2025. For every $1 lost, institutions absorb $3.36 in total. The real challenge in AI fraud detection isn't accuracy. It's latency: ML models add 400ms to every payment decision. That tradeoff is an architecture problem.
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The RPM market hit $36.3B in 2026. Off-the-shelf platforms fail past 12 months: device gaps, static alerts, EHR ceilings. Full CTO's guide to building it right: thebluebox.dev/blog/remote-p…
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Enterprise AI has entered its deployment phase. Inference, not training, is now the primary compute driver. Cost architecture, latency design, and inference reliability are the decisions that determine whether your AI product scales or stalls.
F5 2026: 78% of enterprises now run AI inference as a core operation. The challenge isn't getting AI to work in a demo. It's making inference reliable, observable, and secure at the operational standard of any mission-critical system.
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A single wearable generates 2M data points per day. The AI doesn't fail at the model. It fails at the pipeline. Noise filtering, anomaly thresholding, FHIR context enrichment, HIPAA-compliant transmission. The clinical signal lives in that stack.
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AgTech is having its moment in 2026. Precision farming, AI analytics, autonomous robotics. The gap is not the AI. It is integrating sensor data, yield models, and supply chains that were never designed to connect. That architecture layer is where durable product value gets built.
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Most enterprise AI programs have a governance policy document. Almost none have a working audit trail. A policy describes what should happen. An audit trail is evidence of what actually happened. In 2026, regulators are asking for evidence.
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AcuityMD raised $80M at a $955M valuation. CEO framing: "AI transforms medtech only with the right context, embedded in workflows where decisions are made." The context layer, not the model, is where the defensible MedTech product gets built.
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August 2 is 89 days out. EU AI Act high-risk systems deadline. A proposed Omnibus delay doesn't change the architecture. Audit trails, explainability, human oversight: the AI infrastructure regulated industries require anyway.
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Congratulations Catalina Micheloud on her outstanding results at the II South American Olympic Youth Tournament in Chile! 🏊‍♀️🥇 At The Blue Box, we support Catalina with our sports recovery analysis platform. thebluebox.dev/clients/swima…
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Auryx raised $2M to turn earbuds into health monitors via AI acoustic analysis. The hardware is here. The engineering challenge, acoustic biomarker models and personalization at scale, is where the actual product is built.
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¡Felicitaciones Catalina Micheloud por los resultados en el II Torneo de Promesas Olímpicas Sudamericanas en Chile! 🏊‍♀️🥇 Desde The Blue Box, la acompañamos con nuestra plataforma de análisis de recuperación deportiva. thebluebox.dev/clients/swima…
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Global RegTech investment reached $18.6B in 2024. Most of it went to monitoring infrastructure, not reporting infrastructure. The compliance bottleneck in FinTech isn't detection. Maintaining an audit trail clean enough for defensible automated reporting is the harder problem.
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OpenAI shut down Sora after $15M/day in inference costs against $2.1M lifetime revenue. The subsidized AI era is ending. Which workflows justify frontier model costs is now a first-class architecture decision.
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71% of orgs use generative AI. Only 17% get more than marginal value from it. The gap: AI that cannot access proprietary knowledge. RAG is the architecture that closes this, and in 2026 it is production-critical, not experimental.
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China blocked Meta's $2.5B acquisition of Manus, the largest AI deal ever attempted. Geopolitical AI fragmentation is an active constraint on model sourcing, M&A, and data design. Engineering leaders need to plan around it now.
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