Derisk360
Deployment

4-Layer Intelligence Stack

The 4-Layer Intelligence Stack is Derisk360's architecture for production AI: Layer 01 Data & Context, Layer 02 Decisions, Layer 03 Actions, Layer 04 Outcomes — each built in sequence for governed enterprise deployment.

The 4-Layer Intelligence Stack is Derisk360's architecture for production AI: Layer 01 Data & Context, Layer 02 Decisions, Layer 03 Actions, Layer 04 Outcomes — each built in sequence for governed enterprise deployment.

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OVERVIEW[ 01 / 05 ]

Four layers, built in sequence

Production AI fails when teams skip layers. Chatbots without context hallucinate. Agents without decision memory repeat mistakes. Workflows without governance fail audit. Deployments without outcome measurement cannot prove ROI.

Derisk360 builds every layer because Context and Decisions are where reliable intelligence comes from — not the model alone.

Key takeaways

Layer 01: MCP, knowledge graphs, field governance

Layer 02: Decision memory and systems of record

Layer 03: Multi-agent workflows with audit trails

Layer 04: Value streams and measurable ROI

LAYERS[ 02 / 05 ]

Layer-by-layer breakdown

Layer 01 — Data & Context: Unify source systems via MCP and knowledge graphs. Field mapping, lineage, and access controls prepare governed retrieval for agents.

Layer 02 — Decisions: Combine systems of record with memory of past decisions so agents reason reliably about what to do next.

Layer 03 — Actions: Execute governed, auditable multi-agent workflows with policy engines and human-in-the-loop for high-stakes steps.

Layer 04 — Outcomes: Map agent performance to corporate value streams — ROI, cycle time, error rates — measured continuously in production.

COMPARE[ 03 / 05 ]

Side-by-side comparison.

Comparison of traditional approach and Derisk360 delivery
AspectTraditional approachDerisk360
ContextSample datasets, manual exportsUnified governed context layer via MCP and graphs
EvaluationDemo-day spot checksFDEE-led eval harnesses and policy controls
OperationsTeam disbands after pilot24/7 managed monitoring and tuning
AccountabilitySuccess = proof-of-conceptSuccess = governed production outcomes
HOW WE DELIVER[ 04 / 05 ]

Four phases to production go-live.

01 / PLUG IN

Embed & discover

FDEs embed inside your business, learn the domain, and scope the highest-value use case for this accelerator.

02 / INGEST

Unify context

Connect source systems into a governed context layer — MCP, knowledge graphs, and field mapping in your environment.

03 / BUILD

Configure & evaluate

Build governed agent workflows, run eval harnesses, and tune against your policies before go-live.

04 / RUN

Deploy & monitor

Go live securely in your cloud with FDEE-led monitoring, continuous evaluation, and proactive tuning.

PROVEN[ 05 / 05 ]

Production outcomes, not pilot metrics.

<12wks

Typical accelerator go-live in regulated enterprise environments.

99.98%

Production uptime for governed agent workloads post go-live.

−40%

Faster financial close via agentic reconciliation in banking.

See customer outcomes →

Related resources

Ready for an AI implementation partner?

Book a discovery call and we'll map your highest-value use case — and exactly how we get it into production.

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Frequently asked questions

How does Derisk360 deliver this in production?
Derisk360 embeds Forward Deployed Engineers, runs structured AI accelerators, and implements governed agentic systems in your environment — with evaluation and managed operations built in from day one.
Is Derisk360 a software vendor?
No. Derisk360 is an enterprise AI services firm. You engage us for production outcomes through accelerators and implementations, not licensed shelfware.
How do I start an engagement?
Book a discovery call at derisk360.com/book. We map your highest-value use case and scope an outcome-based accelerator tailored to your industry.
How does 4-layer intelligence stack relate to Derisk360 services?
Derisk360 implements this through AI accelerators and embedded FDEs — book a discovery call to scope your use case.