The tools that make each project possible.

InnerChispa uses local servers, model providers, cloud infrastructure, open-source runtimes, business tools, device integrations and frontend frameworks. This page explains what each category contributes.

Conceptual illustration of EXPLORE IN MORE DETAIL — Conceptual visualization of the area of work.

AMD

Strategic local AI compute direction for heavier inference, coding and reasoning workloads, reducing unnecessary cloud-credit spend.

Intel

Support node for builds, browser review, tests, fallback execution and daily services.

OpenAI, Gemini, Claude, Qwen

Model providers and model families used when advanced capability, reasoning, coding, multimodal or research needs exceed local capacity.

MCP

The connective tissue between assistants, local services, tools, documents and operational state.

Google Cloud and Cloud Run

Public deployment, serverless backend hosting and AI/cloud-native workflow patterns.

Cloudflare

Edge routing, access, DNS/security patterns and public repair paths.

Alibaba Cloud and external infrastructure

Additional cloud capacity and deployment optionality when a project needs it.

Bright Data

Public web/labor-policy monitoring and data-gathering experiments for context-aware products.

MongoDB, Firestore, Supabase

Operational memory, product data stores, experiment data and structured app persistence.

ZKTeco and Hikvision

The bridge to attendance, access control, cameras and physical-world signals.

Technologies in our workAMDIntelOpenAIGoogle CloudCloudflareHome Assistant

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