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iris-harness

PyPIInfrastructure

No liveness check has reached it yet; it is registered on GitHub and PyPI and has been in the index since 11 Oct 2026. How this is checked

iris-harness is an open-source framework for building privacy-first agentic AI assistants with local-first language-model orchestration. It supports agent workflows and integrations using technologies such as LangChain, LangGraph, and Ollama, targeting developers who want self-hosted AI systems.

Inferred · not functionally tested

Open SourceApache-2.0CLISelf-hosted
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Overview

5 features

Purpose: Building privacy-preserving AI assistants that orchestrate local language models and integrations.

Inferred · not functionally tested

Audience: developers building privacy-focused agentic AI assistants

Inferred · not functionally tested

Functions: agents, workflow_automation

Inferred · not functionally tested

Interfaces: API: unknown · MCP: unknown · CLI: indicated (inferred, not tested) · Self-hosting: indicated (inferred, not tested)

Recorded constraints: pricing: open_source · license: Apache-2.0 · platforms: CLI · deployment: cli, self_hosted

Constraint provenance is unknown; confirm requirements with the publisher.

Record sources: pypi.org · github.com. These links do not verify the individual claims.

In the Frameworks & runtimes space, iris-harness takes a focused approach. Inferred · not functionally tested: It focuses on building privacy-preserving AI assistants that orchestrate local language models and integrations. Inferred · not functionally tested: It is built as an open-source project for developers building privacy-focused agentic AI assistants. Basis unknown · not verified: The project is open source (Apache-2.0). Basis unknown · not verified: iris-harness is available on the command line, and it can be self-hosted.

Evarness AI builds and maintains iris-harness, and it first shipped in 2026. Development happens publicly on GitHub with 124 commits in the last 90 days. Inferred · not functionally tested: Among its 5 catalogued features are Local LLM orchestration, agent workflows, and privacy-first design.

Summary written by a language model from the project’s public pages.

Tasks: Inferred · not functionally tested

  • Local LLM orchestration
  • Agent workflows
  • Privacy-first design
  • Integration support
  • React loop

Topics: Inferred · not functionally tested

Tags
local-llmagent-orchestrationprivacy-first-ailanggraphollama
AI capabilities
TextMultimodal
Inference: Local

JSON profile · Text profile · Access guide

Built with & integrations

Framework
FastAPI
AI providers
local_oss
Written with
Claude Code
Runs on
CLISelf-hosted
Written with — evidence
Claude Code
CLAUDE.md

Trust & compliance

License
Apache-2.0
Public signals
HTTPSOpen SourceFree tierGitHubActive maintenance

Indexing history

1

What PulseGate has recorded for this listing

  1. Indexed11 Oct · 21:15 UTC
    iris-harness seen via PyPI Bulk Enumerator
    Source: PyPI Bulk Enumerator · Open

Frequently asked questions about iris-harness

What is iris-harness?
Inferred · not functionally tested: Iris-harness focuses on building privacy-preserving AI assistants that orchestrate local language models and integrations. It is catalogued under Frameworks & runtimes on PulseGate.
Who should use iris-harness?
Inferred · not functionally tested: iris-harness is an open-source project built for developers building privacy-focused agentic AI assistants.
Is iris-harness free?
Basis unknown · not verified: Yes — iris-harness is open source under the Apache-2.0 license and free to use.
What platforms does iris-harness run on?
Basis unknown · not verified: iris-harness runs on the command line. It can also be self-hosted.
Is iris-harness still maintained?
The GitHub repository shows 124 commits in the last 90 days.
Who develops iris-harness?
iris-harness is developed by Evarness AI.
When did iris-harness launch?
iris-harness first shipped in 2026.
Is iris-harness open source?
Basis unknown · not verified: Yes — iris-harness is open source under the Apache-2.0 license, developed on GitHub.

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