VERITY AI · Engineering

Enterprise AI Engineering

Armorstack designs and builds production AI systems — assistants, agentic workflows, and enterprise RAG — with the same governance and security discipline we already apply to cybersecurity and compliance work. Not an AI agency. An engineering practice with a governance program behind it.

Why This Exists

Most AI Initiatives Stall Between Pilot and Production

Organizations don’t usually fail to start AI projects. They fail to finish them — to take a working demo through the integration, security, and governance work that turns it into a system the business can actually run. That work sits at the seam between AI, IT, identity, cybersecurity, and data — exactly the seam Armorstack already owns as a Managed Intelligence Provider.

Enterprise AI Engineering is where that gets built: enterprise AI assistants, agentic workflows, and retrieval-augmented systems designed, integrated, secured, and handed off with governance built in from the first architecture decision — not added after a pilot already works.

Capabilities

What We Design and Build

Six engineering capabilities, delivered individually or as a single governed engagement.

Enterprise AI Assistants

Assistants scoped to a real workflow, with permission-aware access to internal knowledge and systems — not a generic chatbot bolted onto a website.

AI Workflow Automation

Multi-step business processes automated end to end, with human approval points designed in wherever a decision carries real consequence.

Controlled Agentic Systems

Agents with explicit tool authorization boundaries, execution traces, and human checkpoints — controlled agency, not unsupervised autonomy.

Enterprise RAG & Knowledge Engineering

Retrieval built on your actual document and data estate, with permission-aware retrieval so a system never surfaces what a user isn’t cleared to see.

AI Integration Engineering

Connecting AI systems to the identity, data, and business systems you already run — the integration work that determines whether a pilot ever becomes usable.

Secure AI Application Engineering

Prompt-injection defense, data boundaries, output controls, and audit logging engineered into the application — not layered on after deployment.

Technical Approach

Built on an Architecture You Can Audit

Engagements draw from a consistent architectural toolkit — not every project uses every piece of it, but every project is built from the same disciplined set of parts rather than a one-off stack per client:

Model provider selectionSecure inferenceRetrieval-augmented generationAPI & orchestration layersIdentity-aware access & RBACEvaluation & guardrailsObservability & audit evidenceCloud & hybrid deployment

We select the right combination for your environment during scoping — we don’t start from a fixed framework and force your use case to fit it.

Security built in, not bolted on

Prompt-injection defense, data boundaries, tool authorization, and output controls are architecture decisions made during design — not a review performed after a system is already built. Every AI Engineering deliverable is designed to hand off cleanly into SENTRY’s AI security monitoring.See SENTRY AI Security Platform →

Governed from the first decision

Engagements that touch regulated data or consequential decisions are scoped alongside your AI Governance Program and vCAIO oversight where one exists — not governed retroactively once something is already in production.See the AI Governance Program →

Frequently Asked Questions

Is this just custom chatbot development?
No. Chatbots are one possible output of one capability (Enterprise AI Assistants). The practice covers workflow automation, agentic systems, retrieval architecture, integration engineering, and security engineering — scoped to a real business workflow, not a demo.
Do you require us to use a specific AI model or vendor?
No. Model and provider selection is part of scoping, based on your data sensitivity, existing infrastructure, and cost constraints — not a fixed platform we sell regardless of fit.
How does this relate to VERITY AI Launch?
AI Engineering is the design-and-build capability. VERITY AI Launch is a structured, phased engagement that uses this capability to take one specific workflow from business case to governed production. Many clients start with AI Launch; some engage Engineering capabilities directly for a narrower, already-scoped build.
What if we have AI initiatives running across several teams already?
That’s a broader transformation conversation than a single engineering engagement — ask us about our enterprise-wide AI delivery program when we scope your project.

Ready to Build a Production AI System?

Engagements are scoped based on workflow complexity, integration requirements, data sensitivity, and production requirements. Every engagement starts with a scoping call and a written proposal.Request an Engineering Proposal →

Part of Armorstack’s VERITY AI program.