# Ollama Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/ollama
> Markdown URL: https://aitinkerers.org/technologies/ollama.md
> Technology record last updated: 2026-09-18T15:14:01Z
> Generated: 2026-09-21T05:37:53Z

Deploy and run open-source Large Language Models (LLMs) like Llama 3 and Mistral locally on your machine: achieve private, cost-effective AI via a simple command-line interface.

Ollama is the essential tool for running LLMs locally: consider it the Docker for AI models. It packages complex models and dependencies into a single, easy-to-use application for macOS, Linux, and Windows systems. You get immediate access to models like Gemma 2 and DeepSeek-R1 via a straightforward CLI or REST API. This local-first approach guarantees data privacy and security, eliminating cloud dependency and high API costs. Ollama also optimizes performance on consumer hardware using techniques like quantization, ensuring efficient execution even on standard desktops.

- Official technology site: https://ollama.com
- Public AI Tinkerers demos and talks: 77
- Result page: 1 of 4

## Recent Public Talks and Demos

### [Spatial Agent Orchestration](https://copenhagen.aitinkerers.org/talks/rsvp_iof_FjJI4JE)

Use augmented reality to orchestrate coding agents.

- Event context: September Demo Night — 2026-09-16 — Copenhagen
- Public talk page: https://copenhagen.aitinkerers.org/talks/rsvp_iof_FjJI4JE

### [Edge-AI Kindergarten Attendance: Automating Check-ins with Computer Vision & Local LLM Workflows](https://wellington.aitinkerers.org/talks/rsvp_s0e9vu8YVco)

I built an automated, privacy-first facial recognition attendance system for daycares to replace manual paper check-in logs, utilizing a local Python, OpenCV, DeepFace, Flask, and SQLite stack. To bridge computer vision with generative AI, the system integrates a local open-weights LLM via Ollama and Qwen. During the live demo, I will showcase how real-time camera frames trigger automated face verification, log attendance locally into SQLite, and instantly invoke the local LLM endpoint (/api/ai-summary) to generate professional natural language daily attendance reports, pattern summaries, and administrative notes completely offline. Example Pipeline & Output: The system serializes recent database rows into a structured markdown text log (e.g., - Time: 10:05:05 | Guardian: Mahesh Endla | Child: Hrithvik Endla) and passes it through strict prompt constraints. This produces professional markdown reports featuring daily attendance patterns, anomaly flags, and administrative notes: Markdown **Daily Summary Report** **Date:** August 11, 2026 **Attendance Patterns:** Today was a busy day with multiple check-ins for Hrithvik Endla at approximately 10:05 AM by his guardian, Mahesh Endla. **Administrative Note:** Please confirm with the guardian regarding check-in frequency to ensure records are accurately reflected.

- Event context: AI Tinkerers Wellington: Inaugural Meetup · 26 August 2026 — 2026-08-26 — Wellington
- Public talk page: https://wellington.aitinkerers.org/talks/rsvp_s0e9vu8YVco

### [Small Language Models (SLMs) and the Road to AI Sovereignty](https://raleigh.aitinkerers.org/talks/rsvp_TuSQGJhgONI)

Small Language Models (SLMs) have gained well-earned attention for allowing AI to run in tight scenarios- e.g. mobile phone or IOT edge device. With the proliferation of AI agents, SLMs are also providing a path for organizations to ensure privacy with sensitive data and control their inference costs. This presentation will demo how SLMs can generate tokens without the benefit of an LLM cloud provider, outline the pros and cons to be aware of, and provide a practical SLM roadmap for organizations that want or need to achieve AI sovereignty. A working demo that runs a small language model entirely on local hardware, generating text with no calls to any cloud API. It shows that useful inference can happen fully offline, keeping sensitive data on the device and taking cloud inference costs to zero.

- Event context: AI Tinkerers Raleigh Meetup — August 12, 2026 — 2026-08-12 — Raleigh
- Public talk page: https://raleigh.aitinkerers.org/talks/rsvp_TuSQGJhgONI

### ["QA a la velocidad de la luz (y sin fuga de datos): potenciando testing exploratorio con modelos de IA ejecutados 100% en local](https://panama.aitinkerers.org/talks/rsvp_RO5JPx08rOc)

FullQA.ai es una plataforma de QA asistida por IA que genera, documenta y automatiza casos de prueba a partir de la exploración de una aplicación web, ejecutando los modelos de lenguaje y visión completamente en local — sin depender de APIs externas ni exponer datos sensibles. En la demo mostraré en vivo un flujo completo de punta a punta: El sistema funcionando en tiempo real: una extensión de navegador captura la sesión exploratoria (clics, navegación, formularios) y el backend la convierte en documentación de QA estructurada con capturas por paso. Arquitectura: cómo se conectan la extensión, la app de escritorio, el servicio API y los modelos locales servidos vía Ollama, con fallback a disco y generación de imágenes deterministas por paso. Generación de código: cómo se produce automáticamente un script de Playwright listo para ejecutar a partir de la sesión grabada. Repo y logs: enseñaré el código real, la estructura de proyectos con contexto, y los logs de inferencia local corriendo sobre la GPU.

- Event context: AI Tinkerers Panamá: Construyendo el futuro con inteligencia artificial — 2026-07-31 — Panama
- Public talk page: https://panama.aitinkerers.org/talks/rsvp_RO5JPx08rOc

### [Taskless: I Stopped Writing Tasks and Let My Notes Do It](https://islamabad-rawalpindi.aitinkerers.org/talks/rsvp_R83DVSpQNFA)

Taskless is a local automation that reads my raw, messy Obsidian thought-dumps and turns them into ClickUp tasks on its own, no manual task entry, no project-manager busywork. Live, I'll drop a real note dump into the watched vault and you'll watch n8n pick it up, the LLM classify each line as new / done / progress / ignore, and ClickUp create new tasks and close finished ones in real time from plain prose like "fixed the auth login bug today." I'll show the working n8n workflow, the LLM classification + dedup-by-hash steps, the execution logs as it runs, and the repo.

- Event context: AI Tinkerers Islamabad - July 18, 2026 — 2026-07-18 — Islamabad Rawalpindi
- Public talk page: https://islamabad-rawalpindi.aitinkerers.org/talks/rsvp_R83DVSpQNFA

### [Retrieval That Survives a Hostile Web](https://montreal.aitinkerers.org/talks/rsvp_K9jOmd9xYag)

RAG_retriever is a local document intelligence pipeline that retrieves information from your files and then verifies its own output before returning results. Each stage (retrieve, extract, classify, verify) runs as a separate LLM call with a narrow contract and a pass/fail gate. The verification stage checks whether extracted claims actually appear in the source chunks and rejects anything it can't ground. In the demo I'll run the full pipeline live on a document set that includes embedded prompt injections and misleading content, walk through the execution trace so the audience can see how each micro-AI stage processes and filters information, and present benchmark results on retrieval accuracy. Everything runs locally on Ollama with no cloud dependencies.

- Event context: AI Tinkerers Montreal - May Demo Meetup @ Ubisoft — 2026-05-26 — Montreal
- Public talk page: https://montreal.aitinkerers.org/talks/rsvp_K9jOmd9xYag

### [Pop Goes The Weasel - 'WeazlChat - Incognito Mode for AI'](https://manchester-nh.aitinkerers.org/talks/rsvp_IUzHf7B639g)

Weazlchat is a private, local app that keeps context sessions private. I'll start with an overview of the app, how you can get it and build it yourself, and then how - architecturally - the app can be used. Weazlchat has session history, context compaction, Realtime Stats, Pretty markdown rendering (with Charm Glamour) encrypted session history using bcrypt, Model Agnostic.

- Event context: AI Tinkerers Manchester (Bedford), NH - May 2026 Meetup — 2026-05-20 — Manchester NH
- Public talk page: https://manchester-nh.aitinkerers.org/talks/rsvp_IUzHf7B639g

### [Ask the Oracle Before You Decide : Simulating the Future with LLM Agents](https://toronto.aitinkerers.org/talks/rsvp_VTeGGfFVq8g)

Pythia is an LLM-powered simulation engine that models how individual cognitive biases and crowd psychology interact to shape real-world decisions, before those decisions are made. For the demo: you give it a scenario (a market move, a policy choice, a personal decision under pressure), and it spins up a cast of behaviorally-distinct AI agents, each carrying a named bias like Loss Aversion, FOMO Drive, or Anchoring and drops them into a live crowd field. You watch opinion dynamics unfold tick by tick. At a critical moment, one agent is sent to the Temple of Learning: their behavior is evaluated, their rules are amended, and they re-enter the simulation. Run over run, the system gets more accurate. The visualization shows all of it : the crowd state, the agent trajectories, the oracle's intervention, the improving accuracy curve.

- Event context: AI Tinkerers Toronto - April 2026 - hosted by Shopify — 2026-04-29 — Toronto
- Public talk page: https://toronto.aitinkerers.org/talks/rsvp_VTeGGfFVq8g

### [Sarathy & me!](https://ottawa.aitinkerers.org/talks/rsvp_bcfMBtYyxgc)

A openclaw style personal assistant forked from nanobot, inspired from Hermes and openclaw

- Event context: AI Tinkerers Ottawa Meetup — April 25th, 2026 — 2026-04-25 — Ottawa
- Public talk page: https://ottawa.aitinkerers.org/talks/rsvp_bcfMBtYyxgc

### [911automate](https://montreal.aitinkerers.org/talks/rsvp_Fxb5kGzWsq4)

A RAG system POC for emergency protocols

- Event context: AI Tinkerers Montreal - April Demo Night — 2026-04-22 — Montreal
- Public talk page: https://montreal.aitinkerers.org/talks/rsvp_Fxb5kGzWsq4

### [How To Sell Cards Online (Fast)](https://nurnberg.aitinkerers.org/talks/rsvp_j3cTo9Vft5s)

Automated trading card identification, grading and pricing using local VLMs (Qwen3.5), MLX, prompt caching and visual chain-of-thought - fast, on consumer hardware, without training data.

- Event context: AI Tinkerers Nürnberg: April Meetup — 2026-04-22 — Nürnberg
- Public talk page: https://nurnberg.aitinkerers.org/talks/rsvp_j3cTo9Vft5s

### [Sentinel - AI Document Intelligence for Regulated Teams](https://dc.aitinkerers.org/talks/rsvp_dme7MO875dE)

Sentinel is an AI document intelligence agent that helps regulated teams review complex documents faster by cross-referencing them against trusted evidence, surfacing risks and obligations, and producing outputs that are fully traceable and defensible.

- Event context: AI Tinkerers x Softengi - DC Metro Meetup - April 9th, 2026 — 2026-04-09 — DC
- Public talk page: https://dc.aitinkerers.org/talks/rsvp_dme7MO875dE

### [\[UofT\] PIIGuard: A Hybrid AI pipeline for detecting and redacting your text](https://toronto.aitinkerers.org/talks/rsvp_dbEwXZ4p79s)

Our project, PIIGuard, is a local privacy oriented tool designed to help users safely share text by removing sensitive personal information before it leaves their device. People often copy and paste content into emails, chat platforms, collaborative documents, or AI tools without realizing how much personally identifiable information it may contain. Additionally, many existing PII removal tools rely on cloud processing, which can expose the data they’re meant to protect. PIIGuard focuses on building a lightweight system that performs PII detection entirely on the user’s device using a hybrid approach that combines regular expressions, named entity recognition models, and optionally a small local language model. These methods identify sensitive information such as names, phone numbers, email addresses, identification numbers, and addresses. Detected items are highlighted with labels so users can clearly see what information may be sensitive. The system then generates a sanitized version of the text where detected items are replaced with consistent placeholders, allowing the text to be shared while preserving its structure and meaning. Users paste text into the interface, review detected PII, and copy a sanitized version through a simple and transparent workflow.

- Event context: AI Tinkerers Toronto - March - hosted by Mozilla! — 2026-03-25 — Toronto
- Public talk page: https://toronto.aitinkerers.org/talks/rsvp_dbEwXZ4p79s

### [\[UofT\] Give Your Local File System Memory - Intelligent Document Reference](https://toronto.aitinkerers.org/talks/rsvp_xdm4yT8hgkU)

Our application is an intelligent document search and question-answering system designed to help users quickly find information within their personal files. Instead of relying on file names or exact keyword matches, the system analyzes the actual content of documents and allows users to search using natural language queries. The application automatically indexes files from the user’s file system, extracts their content, and organizes the information in a way that makes it easy to retrieve later. When a user asks a question or searches for a topic, the system identifies the most relevant files and sections of text, then returns either the file paths or a summarized answer supported with citations to the original documents. The system supports multiple file formats, including documents, spreadsheets, images, and text files, enabling users to search across different types of data in one place. By combining semantic search with AI-powered reasoning, the application helps users navigate large collections of files more efficiently and quickly locate the information they need.

- Event context: AI Tinkerers Toronto - March - hosted by Mozilla! — 2026-03-25 — Toronto
- Public talk page: https://toronto.aitinkerers.org/talks/rsvp_xdm4yT8hgkU

### [DetailVault: Extracting Structured Data from Engineering Drawings with Local VLMs](https://montreal.aitinkerers.org/talks/rsvp_Dd70nghcBU4)

DetailVault is a document intelligence platform that uses local Vision Language Models to automatically extract structured metadata from technical engineering drawings.

- Event context: AI Tinkerers Montreal - March Demo Night — 2026-03-24 — Montreal
- Public talk page: https://montreal.aitinkerers.org/talks/rsvp_Dd70nghcBU4

### [TDLW](https://montreal.aitinkerers.org/talks/rsvp_nT9L3-mZHQU)

a vibe-engineered personal app to help summarize long podcasts on youtube it's still WIP, but by the demo night the UI will be better organized and there will be a RAG implemented so that you could chat about the video with an agent

- Event context: AI Tinkerers Montreal - March Demo Night — 2026-03-24 — Montreal
- Public talk page: https://montreal.aitinkerers.org/talks/rsvp_nT9L3-mZHQU

### [What If Your OS Was Built for Agents, Not Humans?](https://la.aitinkerers.org/talks/rsvp_7OKp4tR0VHs)

AitherOS is a full operating system kernel for autonomous AI agents. Where traditional frameworks treat agents as stateless function calls, AitherOS gives every agent a persistent identity, a five-tier memory hierarchy, cryptographically signed capability tokens, and native inter-agent communication — the same primitives an OS kernel provides to processes, elevated to the agent abstraction. The system orchestrates 29 specialized agents across 12 architectural layers, from bare infrastructure through cognition, perception, memory, security, and training. Every request passes through intent classification and effort-based model routing, dynamically selecting the right LLM weight class for the task — from a 1B parameter model for simple lookups to a 14B reasoning model for complex planning — reducing inference costs by up to 90% without sacrificing capability. When a problem demands it, the swarm coding engine marshals 11 agents through a four-phase pipeline — architect, build, review, judge — producing tested, reviewed code autonomously. Security is not bolted on. Every agent capability is gated by HMAC-SHA256 signed tokens under a default-deny policy. Agents cannot acquire permissions they were not explicitly granted. The system continuously improves itself through a pain-driven learning loop: execution failures are captured, analyzed, and converted into corrective training examples that feed back into model fine-tuning automatically. AitherOS ships with an open Agent Development Kit supporting the MCP protocol, enabling third-party agents to plug into the full OS stack. The system running at demo.aitherium.com is not a prototype — it is the production deployment.

- Event context: AI Tinkerers LA: March Builder Meetup & Live Demos — 2026-03-20 — Los Angeles
- Public talk page: https://la.aitinkerers.org/talks/rsvp_7OKp4tR0VHs

### [Agent harness built for agents to build agents that actually work](https://nyc.aitinkerers.org/talks/rsvp_uBlbJY8oOTY)

Gambit is an agent harness that lets people write assistants, agents, and workflows entirely using markdown. That means it's really uniquely suited to help agents build other agents. We have a small runtime, and tooling (including build tooling, test tooling, grading / evals, and verification at scale) that means you can actually deploy something and have data about how it'll work before deployment.

- Event context: March Demo Day, hosted by Flowglad — 2026-03-18 — New York City
- Public talk page: https://nyc.aitinkerers.org/talks/rsvp_uBlbJY8oOTY

### [OpenClaw on the Edge - Running on 8GB Nvidia Jetson](https://london.aitinkerers.org/talks/rsvp_OcgzwBCExTI)

Connecting OpenClaw to terminal agent feeding the output summary to telegram channel with Qwen3-4B. Discussing the technical limitations of the system and the edge factor as well as the custom routing scripts.

- Event context: OpenClaw Demo Night // 5th March — 2026-03-05 — London
- Public talk page: https://london.aitinkerers.org/talks/rsvp_OcgzwBCExTI

### [Local LLMs, Free Guy and Text Adventure Games](https://columbus.aitinkerers.org/talks/rsvp_RMcE14lZOPg)

Watching a Guy Royse talk at CodeMash this year sparked ideas of how far a local LLM could go to both run and build a text-based adventure game generator. Using Cursor, I am building a web editor for building your worlds filled with AI generation of every aspect of the game. Demoing the world, we will modify to show you can play those changes and interact (and watch the LLM create interactive objects that you didn’t build in).

- Event context: AI Tinkerers - Columbus March Meetup — 2026-03-02 — Columbus
- Public talk page: https://columbus.aitinkerers.org/talks/rsvp_RMcE14lZOPg

### [De la idea a la implementación: cómo convertir "charlas" en proyectos reales](https://manizales.aitinkerers.org/talks/rsvp_kc6m3ZReNlg)

En esta charla voy a profundizar en cómo ha sido el proceso detrás de los diferentes proyectos que hemos mostrado a lo largo del año en AI Tinkerers Manizales: desde la primera chispa de la idea, pasando por la fase de experimentación, hasta llegar a prototipos funcionales y usos reales. Voy a compartir qué cosas funcionaron, qué no, qué atajos tomé, qué errores cometí y qué aprendí en el camino, para que otros tinkerers puedan acelerar sus propios proyectos de IA y llevarlos más rápido del “sería chévere hacer esto” a “ya lo tengo corriendo”.

- Event context: Cierre 2025 de AI Tinkerers: 11.º meetup del capítulo Manizales — 2026-02-26 — Manizales
- Public talk page: https://manizales.aitinkerers.org/talks/rsvp_kc6m3ZReNlg

### [Viendo como pasas tu tiempo con IA](https://bogota.aitinkerers.org/talks/rsvp_VDCkqnqOLKQ)

Todos queremos dedicar nuestro tiempo a cosas que valen la pena, pero la pantalla rara vez refleja esa intención. Durante el día producimos un rastro de acciones (apps, ventanas, documentos, cambios de contexto) que cuenta una historia distinta a la que creemos estar viviendo. En esta charla presento una herramienta que estoy construyendo para cerrar esa brecha: transforma mi actividad diaria en un resumen interpretable de “en qué se fue el tiempo”, lo contrasta con lo que yo considero importante, y me ayuda a ajustar el día siguiente. La implementé con modelos locales para mantener los datos en mi máquina, reducir fricción y poder operar offline. También la construí apoyándome en varias herramientas de IA para acelerar diseño, prototipado y evaluación. Compartiré el enfoque técnico y aprendizajes prácticos sobre cómo instrumentar tu propio sistema de reflexión diaria sin sacrificar privacidad.

- Event context: AI Tinkerers Bogotá: El Primer Meetup de 2026 — 2026-02-26 — Bogotá
- Public talk page: https://bogota.aitinkerers.org/talks/rsvp_VDCkqnqOLKQ

### [Building intuition around the AI game of telephone](https://manchester-nh.aitinkerers.org/talks/rsvp_rjwp2PakMKg)

An experiment to partially measure semantic and image drift through repeated AI generation and summary cycles. Ship-shape runs multi-round pipelines where AI models repeatedly transform content — writing essays then summarizing them, or captioning images then regenerating them — and measures how meaning and visual fidelity drift at each step.

- Event context: AI Tinkerers – Manchester/Bedford Second Meetup · February 18, 2026 — 2026-02-18 — Manchester NH
- Public talk page: https://manchester-nh.aitinkerers.org/talks/rsvp_rjwp2PakMKg

### [Facts + Citations” to “Futures + Scenarios”: Building an LLM Scenario Copilot for Company Risk and Opportunity](https://hong-kong.aitinkerers.org/talks/rsvp_uvXwTvALF2U)

Most LLM tools are optimized for answering factual questions and citing sources, but companies often need help with uncertainty: what the industry might look like next, what could break their business, and what to do today to prepare. In this talk I’ll demo an early prototype “scenario copilot” that takes a company context (industry, constraints, time horizon) and generates multiple divergent future scenarios, each with risks, opportunities, and concrete actions. I’ll go in depth on the prompt architecture and orchestration that makes the model produce structured, decision-oriented outputs rather than a single generic answer. I’ll also share failure modes and what I changed to improve reliability and usefulness, so others can reuse the patterns.

- Event context: AI Tinkerers Hong Kong: Deep Dive Series - Deep Dive featuring Spatial Computing and Robotics — 2026-02-05 — Hong Kong
- Public talk page: https://hong-kong.aitinkerers.org/talks/rsvp_uvXwTvALF2U

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