SovereignStack builds resilient platforms, secure cloud infrastructure, and the AI systems that run on top of them.
Get in TouchSovereignStack, LLC is a Virginia technology consulting firm. We design, build, and operate production systems across AI, platform engineering, and secure cloud infrastructure.
Engagements are staffed by our principals and senior engineers. SovereignStack brings in specialized subcontractors where an engagement requires capabilities beyond our core team.
AI is part of how every engagement runs, not a bolt-on at the end. Our engineers ship production agents, retrieval systems, and evaluation harnesses as part of standard delivery.
Clean architecture, tested code, and clear documentation are baseline expectations on every engagement. Reviews, CI, and observability are wired in from the first commit.
Clients receive full source code, infrastructure definitions, and runbooks at handoff. No proprietary runtimes, no lock-in to SovereignStack.
Off-the-shelf tools rarely fit regulated or complex operational environments. SovereignStack designs systems around the client's data, controls, and workflows, not the other way around.
Technology should strengthen the people who use it. The firm builds systems that reduce toil for operators and analysts while keeping humans in control of high-consequence decisions.
SovereignStack works with American industry, government, and critical infrastructure buyers. The firm is headquartered in Virginia. All delivery work is performed by US-based engineers.
Full-cycle application design, development, and deployment tailored to your business needs.
Architecture, migration, and management of cloud-native systems on major cloud platforms.
Strategic guidance to modernize legacy systems and adopt emerging technologies.
Embed AI into workflows and products, from LLM-powered features to intelligent automation and data pipelines.
CI/CD pipelines, Kubernetes, and infrastructure-as-code so teams ship quickly with predictable, observable operations.
Fractional CTO and architectural advisory services for organizations that need senior technical leadership without a full-time hire.
Agent orchestration and tool-use standards, retrieval-augmented generation, knowledge graphs, LLM integration across Anthropic and OpenAI models, evaluation harnesses, and agent observability.
Kubernetes at scale with role-based access, network policies, and GPU node pools. Workflow orchestration for ML and data pipelines, container platform migrations, and autoscaling with active cost controls.
Terraform-defined infrastructure on major cloud platforms (AWS, Azure, and GCP), distributed tracing and metrics with OpenTelemetry, least-privilege access control, managed secrets, and network isolation.
SAST, DAST, and SCA integrated into CI/CD, vulnerability governance and ownership attribution, container image compliance, compute image lifecycle automation, and regulated data classification patterns (for example, NPI and PCI).
Vector and lexical search, Postgres with vector and geospatial extensions, Kafka, Spark, event-driven architectures, and knowledge graphs for analyst-grade retrieval.
Python (FastAPI, Flask), Go, TypeScript, and React. Secure single-page application patterns with role-scoped dashboards, API-first backends, and audit-ready access logging.
Most organizations know AI matters. Fewer know where to start. SovereignStack designs, builds, and deploys agents and automation that do real work: processing documents, managing workflows, answering customer inquiries, and executing multi-step decisions at machine speed. Every engagement ships with evaluation harnesses, logging, and a clear ROI model.
Purpose-built agents that work alongside client teams. They handle customer conversations, triage requests, research data, draft documents, and execute multi-step tasks under controlled permissions. Each agent is scoped to the client's domain, data sources, and workflows, with tool-use and retrieval wired in from the first iteration.
Eliminate the repetitive, manual work that consumes operator time. SovereignStack identifies high-impact automation opportunities and builds end-to-end systems for document processing, data entry, approvals, reporting, and system synchronization at scale.
For organizations still scoping where AI fits, SovereignStack runs opportunity assessments, readiness reviews, and phased roadmaps. Recommendations are prioritized by business impact, feasibility, and time-to-value, with a clear handoff to delivery.
Ready to put AI agents to work in your business?
Let's TalkSovereignStack structures engagements around how the client needs to buy and manage the work, not a single delivery model.
Fixed-scope engagements with defined milestones, acceptance criteria, and a handoff plan. Typical work includes platform builds, AI agent systems, cloud migrations, and compliance remediation.
Embedded engineers on the client's team, billed by role: MLOps, platform, backend, AI and agents, and security. Each placement is scoped to a specific role, duration, and reporting line, with SovereignStack providing oversight and backfill.
Technical leadership for organizations that need senior direction without a full-time hire. Engagements cover architecture review, hiring plans, vendor selection, roadmap sequencing, and reporting to boards or investors.
SovereignStack serves as prime on appropriately sized public sector work and as a specialty subcontractor to larger primes. Subcontract roles focus on AI and agent systems, MLOps, platform engineering, and DevSecOps.
Case studies drawn from the principal's prior work. Client names are withheld under standard NDA.
Prior engagement delivered by the principal. On an intelligence analytics platform, the principal led AI tooling that turned large global datasets into strategic risk profiles for analysts. The system combined Kubernetes-based workflow orchestration, vector and lexical search, knowledge graphs, and agent orchestration with least-privilege access to secure data silos. Analyst delivery timelines dropped from weeks to under 24 hours.
Prior engagement delivered by the principal. On a logistics data platform, the principal stood up the first reliable observability baseline, including distributed tracing, platform-wide KPIs, and automated alerting. A data quality audit and remediation effort brought accuracy above 99 percent. Critical import pipeline latency fell from over 30 minutes to under 5 minutes under heavy load, and cloud costs dropped by more than 40 percent with no performance degradation.
Prior engagement delivered by the principal. At a regulated financial services firm, the principal led MLOps and DevSecOps for a 1,000 plus daily user ML platform. Vulnerability ownership and attribution were redesigned across Kubernetes namespaces and CI/CD pipelines, reducing the attributed vulnerability footprint by 85 percent (400 plus findings down to roughly 60) and mean time to remediate by 60 percent. Rolling compute image rehydration on a 100 plus node cluster enforced a 60 day image TTL with zero compliance violations and no maintenance windows. SAST, DAST, and SCA were integrated into every tenant CI/CD pipeline, and a container platform migration to Kubernetes with GPU acceleration cut CPU throttling by 92 percent.
SovereignStack designs and operates systems for environments with formal security and privacy obligations. The firm distinguishes between controls the principal has operated under in prior roles and frameworks used as reference baselines when architecting new systems.
Controls the principal has implemented and operated in production, at enterprise scale, in regulated environments.
Control frameworks the firm uses as reference baselines when architecting new systems, even when a formal audit is not in scope.
Additional frameworks, including FedRAMP, NIST 800-171, and CMMC, are tracked for future federal and defense engagements.
Start a project, request a capability statement, or talk through an idea. We respond to every inquiry within two business days.