Sathus AI 2.0 is now generally available — evaluation harnesses and guardrails included. Explore
We engineer enterprise-grade platforms that solve complex business challenges. Each solution combines deep technical expertise with proven delivery methodologies to ensure measurable impact.
Test sub-10ms microservice endpoints and inspect JSON payloads live
{
"Authorization": "Bearer sth_live_99f8a37b...",
"Content-Type": "application/json"
}{
"task": "audit_lakehouse_compliance",
"agentSwarm": "finance_auditor",
"maxBudgetTokens": 4000
}{
"status": "success",
"agentId": "ag_77a091f",
"executionTimeMs": 14,
"guardrailScore": 0.999,
"decisions": [
{
"step": 1,
"action": "vector_search",
"result": "14 matching policy docs"
},
{
"step": 2,
"action": "audit_check",
"result": "SOC 2 Type II compliant"
}
]
}Each practice is a delivery discipline with accountable outcomes, reference architectures, and a proven path to production.
Pilot AI projects stall in production — models drift, outputs are not auditable, and teams cannot govern them.
Production-grade agentic systems with evaluation harnesses, observability, and human-in-the-loop controls from day one.
Deploy AI with measurable ROI and enterprise-grade governance.
Data lives in fragmented silos with no lineage, no quality guarantees, and no real-time access.
Governed lakehouses and streaming pipelines that turn raw events into trustworthy, query-ready intelligence.
Unified, governed data platform with real-time analytics capabilities.
Generic LLM prompts produce inconsistent outputs and hallucinations that erode enterprise trust.
Custom fine-tuning, RLHF, and enterprise-grade LLM deployment pipelines with automated guardrails.
Domain-specific LLM systems with measurable accuracy and auditability.
Multi-step enterprise workflows require autonomous coordination across tools, APIs, and human approval queues.
Stateful multi-agent swarms with sandboxed tool execution, evaluation harnesses, and human-in-the-loop controls.
Automate complex enterprise workflows with full audit trail and safety guarantees.
Naive vector search retrieves irrelevant context and exposes unauthorized documents to LLMs.
Hybrid BM25 + vector search, semantic reranking, and RBAC permission filtering before prompt injection.
98%+ retrieval precision with SOC 2 document access compliance.
AI agents need secure, standardized connectivity to enterprise APIs without credential exposure.
Custom Model Context Protocol servers, OAuth2 credential vaults, and enterprise MCP gateways.
10x faster agent tool onboarding with 100% audit logging.
Ad-hoc cloud provisioning creates environment drift, security gaps, and uncontrolled spending.
Terraform IaC, GitOps Kubernetes clusters, and automated FinOps policies on AWS and Azure.
99.99% availability with 40% cloud cost reduction through automated governance.
Legacy estates are costly, fragile, and difficult to scale securely without business disruption.
Re-platform to cloud-native architectures on Azure and AWS with zero-downtime migration paths.
Resilient, scalable cloud infrastructure with reduced operational overhead.
Point-to-point APIs and batch ETL create brittle coupling and near-real-time data delays.
Kafka event mesh, Change Data Capture (CDC), and standardized API gateways to decouple systems.
Sub-10ms event delivery with 99.999% message guarantee across enterprise services.
Synchronous legacy APIs bottleneck AI workflows and fail under high-concurrency agentic loads.
Async-first Python FastAPI microservices with Pydantic v2, OpenAPI 3.0, and Redis rate limiting.
50k+ RPS throughput with sub-5ms P99 latency and 100% OpenAPI compliance.
Legacy Oracle and Teradata warehouses incur massive licensing costs and cannot support modern AI workloads.
Open lakehouse migration to Databricks and Snowflake using Apache Iceberg and dual-run validation.
70% TCO reduction and 10x query performance improvement post-migration.
Off-the-shelf software forces process compromise and creates brittle, hard-to-maintain integrations.
Domain-driven applications — custom or composable — that fit the way your organization actually works.
Custom applications that scale with your business complexity.
Strong ideas die in the gap between prototype and a shipped, supported product.
Embedded product squads that take concepts from discovery to GA with a real delivery cadence.
Ship products that users adopt with clear product-market fit signals.
Transformation programs run for years and deliver slide decks rather than measurable outcomes.
Outcome-based roadmaps and durable platform thinking that drives operating-model change.
Measurable transformation with sustainable platform foundations.
Our six-stage delivery process ensures predictable outcomes and continuous value delivery.
Understand your context, constraints, and desired outcomes.
Design reference architectures aligned to your enterprise standards.
Ship production-grade code with automated testing and CI/CD.
Execute zero-downtime rollouts with observability in place.
Run and support your systems with SRE principles.
Continuously improve based on business metrics and feedback.
Our engineering approach sets us apart from traditional consultancies.
We ship production code, not presentations. Every engagement includes source code deliverables, documentation, and knowledge transfer.
Security is built into every layer of our architecture, from secure coding practices to compliance-by-design for regulated industries.
Our reference architectures scale horizontally, integrate cleanly, and adapt to your evolving enterprise requirements.
We stay engaged post-launch to ensure continued success, providing ongoing support, optimization, and evolution of your platform.
Let's discuss how our engineering practices can accelerate your business outcomes.
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