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What we can actually build with

A stack for production systems, not a buzzword list.

AI Model Layer

LLM workflows, retrieval, evaluation, tool use, and private-model planning when the project needs more control.

ClaudeOpenAIGeminiopen-model evaluationmodel routingRAGevalsfunction calling

Agent Infrastructure

Human-supervised agent systems that can research, code, operate tools, and keep context across real work sessions.

Claude CodeMCP serversJarvisNanoOpenClawHermesbrowser automationGitHub toolsapproval gates

Applications

Production web and mobile software with the front-end polish and back-end reliability clients expect.

React 18.3TypeScript 5.9Vite 8Vite+Next.jsNodeFastAPIPhoenixFlutter

Data & Automation

Operational systems that connect CRMs, inboxes, forms, payments, documents, and internal dashboards.

PostgreSQLSupabaseRedisGoHighLevelHubSpotStripen8nMakeZapierwebhooks

Cloud & Ownership

Deployments designed around portability, observability, security, and the right amount of managed service.

DockerTraefikGitHub ActionsDokployregistry.igddev.comVercelAWSS3/MinIOhybrid cloud

Interfaces & Hardware

Experimental systems where agents meet devices, voice, video, robotics, and real-world inputs.

agent control loopsembedded AI prototypesESP32voice agentsvideo understandingWebRTCWebSockets

Applied labs

Emerging tools, evaluated with production judgment.

OpenClaw, NeMoClaw, Hermes, and similar tools are strongest when they are tied to a real workflow: private AI, agentic operations, hardware control, model evaluation, or customer-facing automation.

OpenClaw / Agent Control

Useful for robotics-style control loops, local assistants, hardware interfaces, and supervised tool execution.

NeMoClaw / NeMo-Class AI Ops

A lane for model customization, evaluation, guardrails, and deployment planning when the project justifies it.

Hermes / Open-Model Experiments

Private or local model exploration for teams that need portability, cost control, or more ownership of inference.

How this helps clients

The point is not the stack. The point is leverage.

A strong technology page should make prospects feel that the team can reason about architecture, move quickly, and still leave behind systems that are understandable after launch.

Start with the business workflow, then choose the stack.

Use managed platforms when speed matters and portable systems when control matters.

Keep AI systems observable, reviewable, and grounded in real company data.

Document architecture and tradeoffs so clients are not trapped by mystery code.

Workflow first Integrated systems Global delivery

Bring the hard technical proof into the sales conversation.

We can turn public repositories, prototypes, internal tools, and case studies into a clearer credibility trail for serious prospects.

Build the proof layer