Home/What We Build
Capability Overview · 06 Clusters

The intelligence layer
your operation is missing.

We design, build, and operate AI systems, custom software, data infrastructure, and integrations for organizations whose workflows are too complex, too specific, or too high-stakes for off-the-shelf tools.

Capability Clusters
06
Engagement Models
04
Avg. Time-to-Value
8–12 weeks
Forward-Deployed
Always
Capabilities

Six clusters.
Deployed individually or composed.

Every engagement starts inside your environment, not a slide deck. We ship the smallest valuable operating loop first, then expand.

01 / 06

AI Systems & Agents

Bespoke agents that search, reason, draft, classify, route, and execute inside controlled business workflows.

  • Enterprise agents
  • Workflow copilots
  • RAG systems
  • Knowledge search
  • Agentic automation
  • LLMOps & evals
  • AI governance & guardrails
Explore AI
02 / 06

Operational Software

Custom enterprise platforms for the workflows SaaS can't reach, internal tools, mission dashboards, field ops.

  • Custom platforms
  • Internal tools
  • Mission dashboards
  • Process automation
  • Field operations
  • Legacy modernization
Explore Operational
03 / 06

Data Infrastructure & Intelligence

Pipelines, warehouses, dashboards, and ML models that turn scattered information into decisions.

  • Data pipelines
  • BI & analytics
  • Warehouses & lakehouses
  • Real-time dashboards
  • Predictive analytics
  • MLOps
Explore Data
04 / 06

Systems Integration & Interoperability

Secure system-to-system interoperability for organizations with messy legacy and modern platforms side-by-side.

  • ERP / CRM integration
  • API architecture
  • Middleware
  • Government interoperability
  • Identity & payment exchange
  • Secure data workflows
Explore Systems
05 / 06

Cloud, DevOps & Reliability

Production-grade infrastructure for systems that must be secure, observable, scalable, and cost-controlled.

  • Cloud architecture
  • CI/CD
  • Observability
  • Security hardening
  • Cost optimization (FinOps)
  • Infrastructure as code
Explore Cloud,
06 / 06

Immersive & Digital Experience

Premium websites, 3D/WebGL storytelling, XR training, digital twins, and motion systems.

  • Enterprise websites
  • 3D product storytelling
  • XR / AR / VR training
  • Digital twins
  • Interactive simulations
  • Motion & brand activation
Explore Immersive
Reference Architecture

One operating system,
composed of six layers.

Verne systems are typically organized around this reference architecture. Layers compose: you can engage on a single layer or have us build the full stack against your real environment.

L6Outcomes
Decisions
Dashboards
Reports
Automated Actions
L5Experience
Web Apps
Copilots
Mobile
Field Apps
XR Surfaces
L4Agents
Orchestrator
Tools
Memory
Retrieval
Evaluation
L3Integration
APIs
Middleware
Event Bus
Identity
Audit
L2Data
Lakehouse
Warehouse
Vector Store
Streams
Documents
L1Infrastructure
Cloud
Kubernetes
Observability
Security
FinOps
Engagement Models

How we work with you.

Four contract shapes. All are forward-deployed, Verne engineers work inside your environment with your team, not from a black box.

Recommended

Forward Deployment

Embedded engineers + architects working inside your operation, against your real systems. Typical: 12–24 weeks per system.

Diagnostic

Discovery & Audit

7–10 day systems readiness audit. Maps workflows, data, automation opportunities, and risk surface. Outcome: prioritized roadmap.

Sprint

Build Sprint

Focused 6–10 week sprint to ship a single operating loop end-to-end, agent, integration, dashboard, evals.

Retainer

Steady-State Ops

Ongoing engineering retainer for systems we've shipped, measurement, hardening, evolution, expansion.

Technology Posture

Production-grade stacks. Engineered for audit.

A representative slice of what we run in production. We choose tools per engagement based on environment, compliance, and skill transfer, not vendor allegiance.

Agents & LLMOps
LangGraphDSPyPydantic-AIVercel AI SDKLiteLLMLangSmith / ArizeRagasPinecone / pgvector
Applications
Next.js 15React 19TypeScriptTailwindshadcn/uiThree.js / R3FGSAPFramer Motion
Backends & APIs
Python / FastAPIGoNodePostgresRedisTemporalgRPCGraphQL
Data & ML
SnowflakeBigQuerydbtAirflowDagsterSparkIcebergMLflow
Cloud & SecOps
AWS / Azure / GCPKubernetesTerraformOpenTelemetryCloudflareVercelSOC 2 postureISO 27001 alignment
Integration
Workaton8nApache CamelOpenAPIOAuth / OIDCSAMLKafkaEDI / FHIR / HL7
AI Systems Readiness Audit

Bring us your
most complex workflow.

In 7–10 working days, Verne maps your workflows, data sources, repetitive decisions, automation opportunities, and AI risk areas. You receive a prioritized roadmap showing what to automate, integrate, avoid, and build first.

Tell us what is broken. We will map the system.