Posts tagged with #local ai

Askimo: Ollama Desktop App & GUI for Llama 3, DeepSeek, Mistral & Local AI Models (2026)

Askimo App provides an Ollama GUI for running local AI models like Llama 3.3, DeepSeek R1, Mistral, Gemma 3, Qwen 2.5, and Phi-4. Features persistent history, in-chat search, starred conversations, and export options. Project-aware RAG enables chatting with your codebase or documents using local models with complete privacy. Switch seamlessly between Ollama and cloud providers. Includes lazy loading, custom directives, and automatic endpoint detection.

AI Plans vs AI Agents: When You Need Control, Not Autonomy

AI agents are powerful when the path to an answer is unknown. But for repeatable AI workflow automation - a research report, a code review, a competitive brief - agents fail in practice due to non-deterministic output, retry loops, and unpredictable costs. This post explains the difference between agents and deterministic AI Plans, when to use each, and why Plans are the better default for structured professional work.

How to Connect AI to Real-World Tools with MCP in Askimo Desktop

MCP (Model Context Protocol) lets your AI do real things, not just answer questions. Connect Askimo Desktop to GitHub, databases, local files, web search, and any API via Stdio or HTTP. Secrets stay in your OS keychain. Works with Claude, GPT, Gemini, and local Ollama models.

Chat With Your Documents Using Ollama & RAG: Free Local AI for PDFs, Word Docs & Research Papers

Askimo's RAG (Retrieval-Augmented Generation) with Ollama enables chatting with your documents, research papers, notes, and project files using local AI models like Llama, Mistral, and Phi. Automatically index PDFs, Word documents, spreadsheets, and text files with smart search. Ask questions about your content in plain English - all locally with zero data leaving your machine. Perfect for researchers, writers, students, and anyone managing large collections of documents.

Askimo: Docker Model Runner App & GUI for Local AI (2026)

Askimo App provides a powerful GUI client for Docker Model Runner, Docker's official feature for running AI models locally with OpenAI-compatible endpoints. Features persistent history, in-chat search, starred conversations, and export options. Project-aware RAG enables chatting with your codebase using local Docker AI models with complete privacy. Switch seamlessly between Docker Model Runner and cloud providers.

Best Ollama Clients in 2026: Top 5 Tools

Compare top 5 Ollama desktop clients for 2026. Askimo excels with native performance, multiple AI models support, and RAG-powered project indexing. LM Studio offers easy model management. Open WebUI provides self-hosted team workflows. AnythingLLM focuses on document RAG for chatting with PDFs. Chatbox delivers minimal, lightweight chat. All support local-first privacy but differ in performance, RAG capabilities, and features. Includes setup guides and use-case recommendations.