Cast Net Technology builds and deploys enterprise automation inside your infrastructure. On-prem or hybrid. Document intelligence, audit-grade pipelines, and AI introduced only where constraints and review gates already exist.
Most automation shops add AI early and trust it unconditionally. We invert that. Automation is introduced only where constraints, evidence, and review gates justify it—and never silently. Every output carries provenance. Every ambiguous case surfaces as a flag, not a confident assertion.
Read our governance framework →Each implementation is purpose-built for a vertical where accuracy, traceability, and operator control are non-negotiable. These are deployable accelerators and reference builds—not off-the-shelf software.
On-prem pipeline for chart PDF ingestion, ICD-10 detection, CMS-HCC mapping, and MEAT evidence extraction—with page-level provenance. No PHI to third parties by default.
See reference build →Governed, operator-controlled research systems for systematic financial research—on-prem, evidence-grounded, and built around full operator control. Not financial advice. No execution.
API integration, intermediary services, and dashboard tooling for real-time contractor hours, project burn rates, and budget visibility—running in your environment.
Discuss your workflow →Every engagement follows a structured progression. We do not deploy first and govern later.
Domain audit. Constraint mapping. Data inventory. Integration surface assessment.
Scoped reference build in your environment. Synthetic evaluation dataset. Baseline metrics.
On-prem or hybrid rollout. Your infrastructure, your access controls, your data boundaries.
Shadow mode validation. Regression packs. Operator threshold tuning. Review gate configuration.
Sustained automation with auditability built in. Operator-controlled. Governed by design.
Most AI systems are built to impress in demos. We build for the moment after deployment—when an auditor asks "how did you reach that conclusion?" and a wrong answer has real consequences.
In healthcare, finance, and high-value operations, the cost of a confident wrong answer is asymmetrically higher than the cost of a "needs review" flag. We design for that asymmetry.
Every automated step is introduced only after constraints are defined, edge cases are enumerated, and a deterministic test set validates behavior. Velocity follows rigor, never the reverse.
Policy layers, review gates, kill switches, and shadow mode are first-class features—not afterthoughts. The system supports your judgment; it does not replace it.
The AI Act, CCPA, FTC enforcement actions, HIPAA guidance, and state-level privacy laws don't pause while you're busy building. RuleBrief monitors 50+ federal and state regulatory sources daily and delivers a personalized weekly brief to your inbox — plain-English summaries, color-coded action checklists, and urgent alerts, filtered to your industry and state.
If you're operating AI systems in regulated domains, knowing what the rules require isn't optional. It's the first layer of governance.
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Our Governed intelligence, not guesswork methodology—provenance, constraint-driven automation, shadow mode, and regression-safe releases—is documented and central to every engagement. Read the full governance framework →
Talk to an engineer about your domain, your infrastructure constraints, and what governed automation looks like for your team.