Sathus AI 2.0 is now generally available — evaluation harnesses and guardrails included. Explore
Sathus Technology was founded to solve a fundamental gap: regulated enterprises in finance, healthcare, and critical infrastructure needed to innovate with modern AI and cloud architectures — but lacked access to engineering teams with deep domain expertise and compliance rigor.
Sathus Technology was founded by engineers who had spent years inside global banks, healthcare systems, and insurance firms — watching enterprises spend years on transformation programs that delivered little production value.
We built Sathus around a simple thesis: regulated enterprises deserve production-grade AI and data platforms built by engineers with genuine domain expertise — not management consultants who subcontract development to junior resources.
Every engineer at Sathus has shipped production systems in regulated environments. Every engagement results in systems we stand behind, with clear SLAs and full intellectual property transfer.
Every engagement delivers production source code, automated CI/CD pipelines, and full intellectual property transfer. We do not produce advisory reports without accompanying systems.
Security controls, audit logging, data classification, and RBAC policies are embedded from line one of every system we build — not bolted on at the end of a sprint.
We build on open standards — Apache Iceberg, Delta Lake, FastAPI, Model Context Protocol, and Kubernetes. Your data, intellectual property, and infrastructure remain 100% yours.
We commit to hard technical SLAs: sub-10ms query latencies, 99.99% system availability, 98%+ RAG retrieval precision. These are contractual metrics, not marketing claims.
Our senior engineers integrate directly into your engineering organization — using your Jira, GitHub, and Slack — as a cohesive, high-output extension of your team, not an external agency.
We build for the systems you will operate for the next decade. Every architecture decision considers operational complexity, hiring needs, and long-term maintainability.
Artificial Intelligence
Agentic LLM systems, evaluation harnesses, multi-agent orchestration, RAG pipelines, and Model Context Protocol development.
Data Engineering
Governed lakehouses, Apache Iceberg, Databricks, Snowflake, Apache Kafka streaming, and dbt transformation pipelines.
Cloud Infrastructure
AWS and Azure enterprise landing zones, Kubernetes orchestration, Terraform IaC, GitOps, and FinOps governance.
Enterprise Applications
.NET 9 Clean Architecture, FastAPI microservices, FHIR healthcare APIs, core banking systems, and identity platforms.
Regulated Industries
Financial services (BFSI), healthcare (HIPAA/FHIR), insurance, life sciences, and public sector compliance environments.
Core banking modernization, risk platform engineering, real-time compliance reporting, and anti-fraud ML systems.
FHIR-native data platforms, clinical decision support AI, patient identity management, and regulatory trial data systems.
Actuarial lakehouse analytics, claims processing automation, and IoT-integrated underwriting AI platforms.
Real-time payment processing APIs, PCI-DSS compliant data pipelines, and fraud detection ML inference systems.
A repeatable, phased delivery model that has been refined across engagements in financial services, healthcare, and cloud-native product companies.
Understand your constraints, existing architecture, regulatory obligations, and target business outcomes.
Produce reference architectures aligned to enterprise security and scalability standards with your team.
Ship production-grade code with automated testing, documentation, and CI/CD pipelines from sprint one.
Execute zero-downtime rollouts with observability, alerting, and runbook documentation in place.
Verify against pre-agreed business metric benchmarks — not just functional requirements.
Continuously improve based on production telemetry, cost targets, and evolving business needs.
Book a 30-minute architecture review with our principal engineers. We will evaluate your existing platform, identify high-leverage improvements, and propose a phased delivery roadmap.
