Sathus AI 2.0 is now generally available — evaluation harnesses and guardrails included. Explore
Sathus Technology helps enterprises design, build and modernize AI-powered products, intelligent data platforms and cloud-native applications for regulated industries.
Trusted technologies we design, build and operate on
We do not sell workshops. Each discipline is a delivery practice with accountable outcomes, reference architectures, and a path to production.
Pilot AI projects stall in production — models drift, outputs are not auditable, and teams cannot govern them.
We ship production-grade agentic systems with evaluation harnesses, observability, and human-in-the-loop controls from day one.
Data lives in fragmented silos with no lineage, no quality guarantees, and no real-time access.
We build governed lakehouses and streaming pipelines that turn raw events into trustworthy, query-ready intelligence.
Off-the-shelf software forces process compromise and creates brittle, hard-to-maintain integrations.
We design domain-driven applications — custom or composable — that fit the way your organization actually works.
Legacy estates are costly, fragile, and difficult to scale securely without business disruption.
We re-platform to cloud-native architectures on Azure and AWS with zero-downtime migration paths.
Strong ideas die in the gap between prototype and a shipped, supported product.
We run embedded product squads that take concepts from discovery to GA with a real delivery cadence.
Transformation programs run for years and deliver slide decks rather than measurable outcomes.
We deliver operating-model change through outcome-based roadmaps and durable platform thinking.
We engineer inside the constraints of regulated industries — auditability, data residency, and explainability are design inputs, not retrofits.
Real-time risk, resilient payments rails, and fraud detection built on event-driven platforms.
Regulatory reporting, trustworthy data lineage, and secure multi-tenant platforms.
GxP-aligned data pipelines and compliant machine learning that accelerate R&D.
Interoperable records, consent management, and AI assist under privacy-by-design.
Unified commerce data, demand forecasting, and personalization engines at scale.
IIoT ingestion, digital twins, and predictive quality delivered on the industrial edge.
Production systems our clients run on, plus research that defines what comes next.
Managed platform for building, evaluating, and deploying enterprise agents — with guardrails, evaluation harnesses, and production observability built in.
Unified document intelligence and memory platform that turns enterprise knowledge into grounded, citation-ready context.
Model Context Protocol gateway that connects AI agents to your social and business graph through governed, auditable tools.
Privacy-first identity and consent layer for healthcare ecosystems, designed for interoperability and patient control.
Agentic data governance, industry copilots, and embedded analytics — in active research with design partners.
Every engagement runs on the same governed backbone — so AI, data, cloud, and products compose instead of competing.
A single operating model connecting AI, data, and cloud into composable enterprise products — governed end-to-end by security and a unified API layer. Hover or focus a layer to see how it connects.
The same operating model underpins every engagement — a disciplined process, accountable pillars, and a track record you can verify.
Outcome framing, domain modeling, and a technical spike.
Reference architecture, data contracts, and security design.
Embedded squads shipping in short, reviewable increments.
Evaluations, load, and compliance checks before GA.
Observability, SLOs, and continuous improvement.
We invest in research — agentic systems, data governance, and industry copilots — so clients adopt what is proven, not experimental.
12% of effort in R&D
Definition-of-done includes tests, observability, and documentation. Every release is reviewable and reversible.
100% peer-reviewed
Zero-trust by default, encryption in transit and at rest, and an audit trail on every action.
SOC 2 Type II
2018
Founded as a product engineering studio for regulated enterprises.
2020
First enterprise data platform reaches production with full lineage.
2022
Launched the Sathus AI research practice and evaluation harnesses.
2024
ISO 27001-aligned security program and responsible-AI controls.
2026
Agentic platforms operating across six regulated industries.
We are not framework-agnostic for its own sake. We go deep on a curated set of platforms and operate them in production.
Sathus Technology is a principal software engineering firm specializing in accountable, production-ready AI agent swarms, Apache Iceberg data lakehouses, and zero-downtime cloud platform modernization.
Procurement and partnership start with trust. We make our posture legible, reviewable, and verifiable.
Zero-trust architecture, encryption in transit and at rest, and continuous monitoring with full audit trails on every action.
Data minimization, residency controls, and consent you can audit — privacy is an architecture decision, not a policy.
SOC 2 Type II and ISO 27001-aligned controls, with GDPR and HIPAA-ready patterns for regulated programs.
Defense-in-depth reference architectures, reviewed jointly with your risk and security teams before build.
Model cards, evaluation suites, and human oversight by design — so AI decisions are explainable and contestable.
Practices, patterns, and postmortems from building AI and data platforms for regulated enterprises.
Change data capture with provenance end-to-end.
Identity, segmentation, and audit by default.
Closing the gap between raw events and decisions.
A phased, reversible path off legacy infrastructure.
Bring us a problem worth solving. We will map the architecture, the data, and the path to production — in a single strategy session.
No vendor pitch. A working session with our principal engineers.
