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.
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.
Turn forms, scans, and free text into structured data
OCR, entity extraction, classification, and redaction pipelines — built on Azure AI Foundry and AWS AI services, or self-hosted models where data can’t leave the boundary.
OCR & Document Extraction
Text, tables, and key-value pairs pulled from scanned PDFs, forms, and images with layout awareness — Azure AI Document Intelligence, Amazon Textract, or open-source engines.
Named Entity Recognition (NER)
People, organizations, locations, dates, identifiers, and custom domain entities extracted and linked — Azure AI Language, Amazon Comprehend, or fine-tuned models for your terminology.
PII Detection & Redaction
Automatic identification and masking of sensitive data for FOIA releases, records requests, and data-sharing — with a reviewable audit trail.
Classification & Routing
Documents and messages sorted by type, sensitivity, or topic to drive workflows, retention, and case management.
Translation & Transcription
Speech-to-text and machine translation for multilingual intake and media — Azure AI Speech / Translator and Amazon Transcribe.
Extraction Pipelines
The above chained into monitored, evaluated pipelines — human-in-the-loop review, confidence thresholds, and metrics wired into CI.
We build on the platforms your agency already trusts
Azure AI Foundry — model catalog, Azure OpenAI, agent service, prompt flow, and built-in evaluations, deployable in Azure Government.
AWS AI services — Amazon Bedrock and SageMaker for models, plus Textract, Comprehend, Rekognition, and Transcribe for documents, language, vision, and speech — available in AWS GovCloud.
Where a managed service isn’t an option, the same capabilities run on self-hosted, open-source models inside your boundary.
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.
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.