JarvisBot

JarvisBot - AI assistant that grows smarter with your community’s input. It turns everyday interactions into structured signals-ratings, corrections, and examples-so the underlying models can be refined. Designed for teams, creators, and communities, it focuses on practical workflows: drafting, Q&A, knowledge retrieval, and lightweight automation.

JarvisBot introduces a feedback-first workflow where users guide responses and supply better versions, helping the system learn preferred tone, accuracy, and format. Moderation tools let admins curate training data, protect private information, and roll out improved model presets when ready. As quality rises, contributors receive tangible perks-higher limits, priority processing, or gated features-which reinforces a positive loop of participation and model improvement.

• Reactions, edits, and examples are converted into training signals.
• Admins approve changes before model presets are promoted to everyone.
• Answers adapt to user roles (member, editor, admin) and context.
• Configurable filters, citation prompts, and style rules reduce noise.
• Contributors unlock higher quotas, tools, or access tiers.

Under the hood, JarvisBot logs supervised signals (thumbs, corrections, exemplars) with metadata such as topic, channel, and role. A training pipeline aggregates this data into preference pairs and instruction examples, then periodically re-scores responses across evaluation sets. Rollouts happen via versioned presets, so teams can A/B test improvements and rollback if needed. Data handling is opt-in, with redaction for sensitive fields and retention windows set by admins. Webhooks and API endpoints allow exporting feedback, importing knowledge snippets, and integrating custom evaluators to enforce domain style or compliance rules.

Working link to JarvisBot on Telegram. The number of active users is not disclosed. If the app is not working or the description seems incorrect, let us know.