Structured Query
Translates natural‑language questions into queries against your ERP records, CRM tables, service logs, and anything that lives in rows and columns.
Product
Private, Governed AI Infrastructure
ARGUS is a private AI platform that runs inside your network. It brings together the four things you need to put AI to work on your own data—local model inference, retrieval across your existing systems, governance and access control, and operational observability—into one product you run inside your own network.
The Platform
Four Pillars. One Product. Three Ways to Buy.
Organizations in Manufacturing and regulated‑industries have decades of operational data and the same pressure to use AI as everyone else—but cloud AI poses sovereignty, procurement and security & privacy challenge's— shipping valuable knowledge to a model vendor is a bad trade. Enterprise alternatives were built for Fortune 500 budgets and assume a dedicated data, AI, and platform team to assemble them.
Enter ARGUS.
Private AI Inference
“Your models. Your hardware. Your data.”
ARGUS runs models on your own hardware—open models for generation, local embeddings, and a configuration toggle to use approved cloud model providers when, and only when, you choose to. Air‑gapped and low‑egress deployments are first‑class. Outbound connectivity is opt‑in, capability by capability.
Data Integration & Natural‑Language Query
“Ask in plain English. Across every system.”
Connect ARGUS to your existing systems and let users query them in plain English. The platform interprets each request, dispatches it across the right capabilities in parallel, assembles the results, and streams the answer back—structured records, document search, time‑series analysis, geospatial reasoning, and live web enrichment when permitted. New datasets are added through a guided import flow.
Governance & Access Control
“Who sees what. Who asked what. Logged.”
Role‑aware administration, workspace‑scoped prompts and settings, access control on every workspace and dataset, and a policy layer that decides which users can see which data. For cloud‑bound model calls, a redaction layer scrubs sensitive content before anything leaves the building—every redaction decision is logged.
Observability & Guardrails
“Every prompt. Every decision. Auditable.”
Every prompt, model call, dataset access, redaction decision, and administrative change emits a structured audit event. Health checks across every running capability, usage tracking by user and model, prompt‑injection defenses, and policy hooks that govern how queries are interpreted. When the auditor or a key customer asks what the AI did and what it saw, the answer comes with evidence.
What’s Inside
Capabilities, Surfaces, and a Deployment Shape That Doesn’t Require a Platform Team.
Capabilities ship as versioned, independently‑managed bundles. Adding, upgrading, or removing one is a console operation—not a platform redeploy.
Knowledge Search
Semantic search across documents, manuals, case files, contracts, troubleshooting notes, and any unstructured corpus you put behind it.
Synthesis
Turns retrieved data into the output the user asked for—a plain answer, an executive summary, a briefing table, a structured report, or a campaign payload.
Time‑Series Intelligence
Anomaly detection and forecasting on machine, sensor, or process‑level data—ready to feed predictive maintenance and operations workflows.
Geospatial Reasoning
Routing, points‑of‑interest analysis, isochrones, clustering, and route planning for territory and field‑ops use cases.
Web Enrichment
Live web search added to an answer when the workspace and deployment profile allow it—disabled or unreachable in restricted environments.
Surfaces
Unified shell for single sign‑on across every surface. Workspace‑driven chat for purpose‑shaped experiences—BI, Reports, Executive, Daily Briefing, Campaigns, Operator, Diagnostic, Alerts, Import. Admin console for agents, capability bundles, health, usage, users, workspaces, and datasets—each tab role‑aware so common configuration doesn’t require code changes. Dataset import, campaign management, and an embedded workflow scheduler round out the surfaces.
Deployment
ARGUS is delivered as a single containerized stack that runs on a workstation in your network. Deployment profiles cover local‑GPU, local‑CPU, and air‑gap‑oriented configurations. The whole thing fits on a single dual‑GPU workstation for production. A pre‑built appliance is on the roadmap.
Who It’s For
Companies with Valuable Proprietary Data, a Real Reason to Keep It Local, and No Internal AI Platform Team.
Manufacturers
Companies with years of operational and customer data scattered across systems of record. A digital‑transformation initiative stalled on data plumbing or governance—not on appetite.
Regulated Industries
Organizations operating under data‑sovereignty, residency, or audit requirements that make cloud AI a non‑starter. Local pilots stuck without the governance plumbing to put them into production.
How We’re Different
Same Outcome. Without the Enterprise Budget or Timeline.
ARGUS sits between cloud AI services that won’t keep your data on‑prem and enterprise stacks that won’t fit your budget—packaged for organizations without a platform team to assemble it themselves.
vs. Cloud AI Services
Cloud AI: Your data on someone else’s servers
ARGUS: Local‑first inference and retrieval, with audit trail in the platform
vs. Enterprise Private‑AI Stacks
Enterprise: Seven‑figure budget, year of platform engineering
ARGUS: Same private‑inference outcome—without the seven‑figure budget or year of platform engineering
vs. DIY Open‑Source
DIY: Real and capable—but a job in itself
ARGUS: Packaged with integration, access control, audit, and admin workflows
vs. Per‑Token Pricing
Cloud: Per‑query costs and token bills that scale with usage
ARGUS: Flat per‑user pricing or a one‑time license—costs you can predict
Your Data. Your Expertise. Your AI. It Should Stay Yours.
Schedule a 15‑minute conversation. We’ll learn your operations and show you what ARGUS can do with the data you already have—no commitment, no pitch.
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