Sathus AI 2.0 is now generally available — evaluation harnesses and guardrails included. Explore
Find answers to common questions about our AI platform, data lakehouse architectures, cloud security, and embedded engineering squads.
No. Sathus AI operates under strict zero-retention policies. Customer data is processed in-memory, never stored, and never used to train third-party or foundational LLM models.
Model Context Protocol (MCP) is an open standard created by Anthropic that standardizes how AI agents communicate with external APIs, tools, and databases with secure authorization.
Our evaluation harnesses continuously benchmark LLM outputs against curated ground-truth datasets, measuring factual accuracy, Toxicity, PII leakage, and rule adherence before responses reach end users.
An Apache Iceberg lakehouse is an open table format that brings SQL ACID transactions, time travel, schema evolution, and high performance to cloud object storage (S3/Azure Data Lake), eliminating proprietary warehouse lock-in.
We deploy dual-execution streaming pipelines running parallel row-level checksum comparisons for 30+ days before cutting over traffic from legacy systems.
Yes. Sathus Technology maintains a audited SOC 2 Type II control environment and executes Business Associate Agreements (BAAs) with all healthcare clients.
Our senior principal engineers, data architects, and product leads integrate directly into your Jira, GitHub, and Slack workflows as a cohesive, high-output delivery squad.
Speak directly with our engineering team or schedule a dedicated strategy consultation.
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