ai.deployment = private & compliant

LLM applications & AIOps, engineered for security

We build large-language-model applications — assistants, agents, and document intelligence — and apply AI to operations: anomaly detection, predictive scaling, and automated incident response. Deployed in your cloud or GovCloud boundary, not a third party's.

// the AI stack we deploy
LLMs (open & hosted) RAG & vector search Agents & tool use Guardrails & eval Private / self-hosted inference MLOps & observability NIST AI RMF
LLM Application Development

AI products, built to survive contact with production

Not demos — retrieval-grounded, evaluated, monitored, and secured.

RAG & Document Intelligence

Retrieval-augmented assistants over your policies, contracts, and knowledge bases — with citations, access controls, and freshness.

Assistants & Agents

Task-oriented copilots and multi-step agents with tool use, human-in-the-loop approval, and bounded permissions.

Private & Compliant Deployment

Self-hosted or GovCloud inference so prompts and data never leave your boundary. Air-gapped options for classified environments.

Guardrails & Safety

PII detection and redaction, prompt-injection defense, output filtering, and policy enforcement at the gateway.

Evaluation & Testing

Groundedness, accuracy, and regression test suites in CI — every model or prompt change is measured before it ships.

Integration & APIs

LLM capability wired into existing apps, workflows, and mobile products — on the secure infrastructure we already build.

AIOps

AI applied to operations

Turn logs, metrics, and traces into detection, prediction, and automated response.

Anomaly Detection

Model-based baselining on metrics and log streams to catch incidents before thresholds or users do.

Alert Noise Reduction

Correlation and deduplication that collapses alert storms into a single, actionable signal with probable cause.

Predictive Scaling & Capacity

Forecast demand and cost, right-size ahead of load, and feed the numbers back into FinOps.

Automated Remediation

Runbook automation and safe auto-rollback wired to the CI/CD pipeline — with guardrails and audit trails.

Root-Cause Assist

LLM-assisted triage that summarizes what changed, links the deploy, and drafts the incident timeline.

MLOps Foundations

Model registry, pipelines, drift monitoring, and rollback — the same rigor we bring to application delivery.

Responsible & Secure AI

Built to the standards you answer to

Our AI work aligns with the NIST AI Risk Management Framework and your agency's data-governance requirements — documented model risk, data lineage, human oversight, and evaluation evidence you can hand to an assessor.

Have an AI use case or a noisy ops problem?

Tell us the workflow, the data, and the constraints. We’ll come back with an approach, an evaluation plan, and a clear quote or SOW.