{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_halist-ai","slug":"halist-ai","name":"Halist AI","type":"product","url":"https://halist.ai","page_url":"https://unfragile.ai/halist-ai","categories":["chatbots-assistants"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_halist-ai__cap_0","uri":"capability://text.generation.language.multi.model.conversation.aggregation.with.unified.interface","name":"multi-model conversation aggregation with unified interface","description":"Halist AI implements a model-agnostic conversation router that abstracts away differences between Claude, GPT-4, Llama, and other LLMs behind a single chat interface. The system maintains a unified conversation history and allows users to send the same prompt to multiple models simultaneously or sequentially, comparing outputs without context switching. This is achieved through a standardized message format that translates user input into provider-specific API schemas (OpenAI's chat completion format, Anthropic's messages API, etc.) and normalizes responses back to a common structure.","intents":["Compare how different AI models respond to the same prompt without opening multiple tabs or apps","Switch between Claude, GPT-4, and open-source models mid-conversation to find the best fit for a task","Maintain a single conversation history across multiple model backends for audit and reference"],"best_for":["Developers evaluating multiple LLMs for production use","Researchers comparing model capabilities and outputs","Privacy-conscious professionals who want to avoid vendor lock-in"],"limitations":["Response latency increases with multi-model queries due to sequential or parallel API calls to different providers","No built-in cost optimization — users pay per-token to each provider independently without aggregated billing","Model-specific features (e.g., Claude's vision, GPT-4's plugins) may not be fully exposed through the unified interface"],"requires":["Valid API keys for at least one supported model provider (OpenAI, Anthropic, or local Ollama instance)","Network connectivity to model provider APIs or local LLM server","Halist AI account for conversation persistence"],"input_types":["text prompts","conversation history (JSON or proprietary format)"],"output_types":["text responses","structured comparison data (model name, response time, token count)"],"categories":["text-generation-language","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_halist-ai__cap_1","uri":"capability://safety.moderation.privacy.preserving.local.conversation.processing","name":"privacy-preserving local conversation processing","description":"Halist AI provides an optional local processing mode where conversation history and user prompts are encrypted and stored on the user's device rather than transmitted to Halist's servers. The architecture uses client-side encryption (likely AES-256 or similar) to encrypt conversations before any network transmission, with decryption keys managed locally. When users opt for local-only mode, API calls to LLM providers (OpenAI, Anthropic) are routed directly from the client without intermediation, ensuring Halist servers never see the conversation content—only metadata like API usage.","intents":["Store sensitive conversations (legal, medical, financial) without trusting a third-party platform with plaintext data","Ensure conversations remain private even if Halist's servers are compromised or subpoenaed","Comply with data residency and privacy regulations (GDPR, HIPAA) by keeping data on-device"],"best_for":["Legal professionals handling privileged communications","Healthcare workers discussing patient information","Enterprise security teams evaluating AI tools for sensitive workflows"],"limitations":["Local encryption adds computational overhead (~50-200ms per message depending on key size and device capability)","Cross-device synchronization is limited or disabled in full local mode to prevent encrypted data exposure","Users are responsible for device security — local encryption is only as strong as the device's physical and OS-level security","No server-side backup of encrypted conversations — device loss means conversation loss unless user manually exports"],"requires":["Device with sufficient storage for local conversation database (typically <100MB for thousands of conversations)","Operating system with native encryption support (Windows 10+, macOS 10.12+, iOS 13+, Android 9+)","Halist AI client version 2.0+ with local encryption feature enabled"],"input_types":["text prompts","file uploads (if supported, encrypted before storage)"],"output_types":["encrypted conversation database (proprietary format)","plaintext responses (decrypted locally for display)"],"categories":["safety-moderation","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_halist-ai__cap_10","uri":"capability://memory.knowledge.conversation.sharing.with.granular.access.control","name":"conversation sharing with granular access control","description":"Halist AI allows users to share conversations with others via shareable links or direct invitations, with granular access control (view-only, edit, comment). Shared conversations can be encrypted or public depending on user preference. The system supports role-based access (owner, editor, viewer) and time-limited sharing links that expire after a set duration. Shared conversations maintain a separate access log showing who accessed the conversation and when.","intents":["Share AI-assisted work with colleagues or clients for feedback without exposing full account access","Collaborate on conversations with team members who can add responses or comments","Create time-limited shareable links for temporary access (e.g., for client presentations)"],"best_for":["Teams collaborating on projects using AI assistance","Consultants and agencies sharing work with clients","Researchers sharing conversation datasets with collaborators"],"limitations":["Shared conversations are stored on Halist's servers, requiring trust in Halist's security and privacy","No end-to-end encryption for shared conversations—Halist can theoretically access shared content","Access control is coarse-grained (view/edit/comment); no field-level or response-level permissions","Shared conversations can't be revoked retroactively if links are leaked; only future access can be blocked"],"requires":["Halist AI account with at least one conversation","Recipient email address or shareable link (for public sharing)"],"input_types":["conversation selection","access level (view-only, edit, comment)","recipient email or public link generation","optional expiration date"],"output_types":["shareable link or invitation email","access log (viewer, timestamp, action)","shared conversation view (with access restrictions enforced)"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_halist-ai__cap_11","uri":"capability://text.generation.language.conversation.summarization.and.topic.extraction","name":"conversation summarization and topic extraction","description":"Halist AI automatically generates summaries of long conversations and extracts key topics/themes using NLP techniques (likely abstractive summarization via a smaller LLM or extractive methods). Summaries are generated on-demand or automatically for conversations exceeding a certain length, and are displayed in conversation metadata. Topic extraction identifies key concepts, entities, and themes discussed in the conversation for tagging and organization purposes.","intents":["Quickly understand the gist of a long conversation without reading the entire transcript","Automatically extract topics for conversation organization and search","Generate executive summaries of conversations for sharing with stakeholders"],"best_for":["Users with long, complex conversations who need quick summaries","Teams managing large conversation repositories who need automated organization","Professionals generating reports or summaries from AI-assisted work"],"limitations":["Automatic summarization may lose important nuances or context from long conversations","Topic extraction is generic and may not capture domain-specific concepts","Summarization adds latency (100-500ms per conversation depending on length)","No user control over summary length or style—summaries are generated with fixed parameters"],"requires":["Halist AI account with at least one conversation","Optional: GPU acceleration for faster summarization (CPU-only is slower)"],"input_types":["conversation content (full transcript)"],"output_types":["summary text (1-3 paragraphs)","extracted topics (list of key concepts)","summary metadata (generation timestamp, confidence score)"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_halist-ai__cap_2","uri":"capability://memory.knowledge.cross.platform.conversation.synchronization.without.cloud.lock.in","name":"cross-platform conversation synchronization without cloud lock-in","description":"Halist AI synchronizes conversations across desktop (Windows, macOS, Linux), mobile (iOS, Android), and web clients using a decentralized or hybrid sync architecture. Rather than forcing all data through Halist's servers, the system uses optional cloud sync (with encryption) or peer-to-peer sync via local network protocols (e.g., WebRTC, local network APIs). Users can choose to sync only specific conversations or devices, and the sync mechanism respects local-first principles—conversations are always stored locally first, with optional cloud backup for convenience.","intents":["Continue a conversation started on desktop on mobile without re-authenticating or losing context","Selectively sync only work conversations to cloud while keeping personal conversations local-only","Maintain conversation access even if cloud sync is disabled or Halist's servers are unavailable"],"best_for":["Remote workers and consultants who switch between devices throughout the day","Teams that need conversation sharing without centralizing data on corporate servers","Users in regions with unreliable internet who want offline-first sync"],"limitations":["Sync conflicts may occur if the same conversation is edited on multiple devices simultaneously—conflict resolution strategy is unclear from available documentation","Cross-platform sync latency depends on network conditions; local-network sync is faster but requires devices on same WiFi","Mobile clients may have reduced sync frequency to preserve battery life, causing temporary inconsistencies","Selective sync requires manual configuration per conversation, adding friction for users with many conversations"],"requires":["Halist AI client installed on at least two devices","Same account credentials across devices","Optional: Local network connectivity for peer-to-peer sync, or internet access for cloud sync","Sufficient device storage for local conversation copies"],"input_types":["conversation metadata (timestamps, model used, participant info)","encrypted conversation content (if cloud sync enabled)"],"output_types":["synchronized conversation state across devices","sync status indicators (in-progress, completed, failed)"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_halist-ai__cap_3","uri":"capability://automation.workflow.freemium.rate.limiting.with.tiered.api.quota.management","name":"freemium rate-limiting with tiered api quota management","description":"Halist AI implements a freemium model with rate limits enforced at the API gateway level, tracking per-user token consumption and request counts across all model providers. Free tier users receive a monthly quota (e.g., 100K tokens or 50 requests) that resets on a calendar basis, while paid tiers unlock higher limits or unlimited access. The system uses a quota tracking service that monitors real-time consumption and blocks requests when limits are exceeded, with clear messaging about remaining quota and upgrade paths.","intents":["Offer free access to multi-model AI for casual users while monetizing heavy usage","Prevent abuse and ensure fair resource allocation across the user base","Provide transparent quota visibility so users understand their usage and upgrade incentives"],"best_for":["Freemium SaaS products seeking sustainable monetization without paywalls","Teams evaluating Halist for pilot projects before committing to paid plans","Individual developers and students with light AI usage needs"],"limitations":["Free tier rate limits force conversion to paid plans faster than competitors (e.g., ChatGPT Plus offers higher free limits), reducing organic adoption","No granular per-model quotas—a single quota pool across all models means users can't prioritize cheaper models (Llama) over expensive ones (GPT-4)","Quota resets on calendar basis rather than rolling window, creating cliff effects where users hit limits mid-month","No quota sharing or team pooling—each user has independent quotas, limiting collaborative use cases"],"requires":["Halist AI account with verified email or payment method","Active internet connection to validate quota status with Halist servers","Client-side quota tracking (optional, for offline awareness)"],"input_types":["API requests with user authentication token","token count metadata from LLM provider responses"],"output_types":["quota status (remaining tokens, requests, reset date)","rate-limit headers (HTTP 429 when exceeded)","upgrade prompts and pricing information"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_halist-ai__cap_4","uri":"capability://tool.use.integration.provider.agnostic.api.key.management.with.credential.isolation","name":"provider-agnostic api key management with credential isolation","description":"Halist AI provides a secure credential management system where users can add API keys for multiple LLM providers (OpenAI, Anthropic, local Ollama) through a unified settings interface. Keys are encrypted at rest using a user-specific encryption key derived from their account password, and are never logged or transmitted to Halist's servers in plaintext. The system supports both user-managed keys (users provide their own API keys) and Halist-managed keys (Halist provides shared API access with usage tracking). Each provider integration includes validation logic to test key validity before storing.","intents":["Use personal API keys with Halist without exposing them to Halist's infrastructure","Switch between personal and Halist-managed API keys depending on cost/privacy preferences","Revoke or rotate API keys without losing conversation history or account access"],"best_for":["Enterprise users with strict API key management policies","Developers who want to use Halist as a frontend to their own LLM infrastructure","Cost-conscious users who want to use their own API keys to avoid Halist's markup"],"limitations":["User-managed keys require users to maintain their own API key security and rotation—Halist cannot help if keys are compromised","No built-in key rotation or expiration management—users must manually update keys when providers rotate them","Halist-managed keys add a trust requirement; users must trust Halist not to abuse shared API access","No audit logging of which conversations used which API keys, limiting compliance visibility"],"requires":["Valid API key from at least one supported provider (OpenAI, Anthropic, Ollama, etc.)","Halist AI account with secure password (for key encryption)","Network connectivity to validate keys with provider APIs"],"input_types":["API key strings (plaintext input, encrypted before storage)","provider selection (OpenAI, Anthropic, Ollama, etc.)"],"output_types":["encrypted key storage confirmation","key validation status (valid, invalid, expired)","provider availability indicators"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_halist-ai__cap_5","uri":"capability://memory.knowledge.conversation.export.and.portability.with.multiple.format.support","name":"conversation export and portability with multiple format support","description":"Halist AI allows users to export conversations in multiple formats (JSON, Markdown, PDF, plaintext) for archival, sharing, or migration to other platforms. The export system preserves conversation metadata (timestamps, model used, token counts) and supports selective export (single conversation or bulk export of all conversations). Exported files are generated client-side when possible to avoid transmitting conversation content to Halist servers, and include optional encryption for sensitive exports.","intents":["Archive important conversations for long-term reference or compliance purposes","Share conversation excerpts with colleagues or clients in readable formats","Migrate conversations away from Halist to another platform or local storage without data loss"],"best_for":["Professionals in regulated industries (legal, healthcare) who need conversation archives","Teams collaborating on projects and needing to share AI-assisted work","Users concerned about vendor lock-in who want portable conversation data"],"limitations":["PDF export may lose formatting or interactive elements if conversations contain code blocks or structured data","Bulk export of thousands of conversations can be slow and memory-intensive on client devices","Exported JSON format is proprietary to Halist—no standardized conversation format for cross-platform compatibility","Encrypted exports require users to manage decryption keys separately, adding complexity"],"requires":["Halist AI account with at least one conversation","Sufficient device storage for exported files (typically 1-10MB per 100 conversations)","Optional: PDF export requires additional client-side rendering library"],"input_types":["conversation selection (single or bulk)","export format preference (JSON, Markdown, PDF, plaintext)","optional encryption password"],"output_types":["exported files in selected format","metadata files (conversation index, export timestamp)","optional encryption wrapper"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_halist-ai__cap_6","uri":"capability://tool.use.integration.local.ollama.integration.with.self.hosted.model.support","name":"local ollama integration with self-hosted model support","description":"Halist AI integrates with Ollama, an open-source framework for running LLMs locally, allowing users to add self-hosted models (Llama 2, Mistral, etc.) to their model roster without API costs. The integration works by discovering Ollama instances on the local network or via explicit host configuration, and routing prompts to local models using Ollama's REST API. Users can mix local models with cloud-based providers in the same conversation, enabling cost optimization (use free local models for drafting, expensive cloud models for refinement).","intents":["Run AI models locally to avoid API costs and maintain complete data privacy","Combine local and cloud models in a single workflow for cost-optimized inference","Use open-source models (Llama, Mistral) without relying on proprietary APIs"],"best_for":["Developers and researchers with GPU hardware who want to self-host models","Organizations with strict data residency requirements","Cost-conscious users willing to manage local infrastructure"],"limitations":["Requires GPU hardware (NVIDIA, AMD, or Apple Silicon) for reasonable inference speed; CPU-only inference is slow (minutes per response)","Users must manage Ollama installation, model downloads, and hardware maintenance—no managed service","Local models are typically less capable than GPT-4 or Claude, limiting use cases for complex reasoning","Network latency between Halist client and local Ollama instance can add 100-500ms per request","No automatic model selection or fallback if local model fails—users must manually switch to cloud models"],"requires":["Ollama installed and running locally (https://ollama.ai)","GPU with sufficient VRAM for model (8GB+ for Llama 2 7B, 16GB+ for larger models)","Network connectivity between Halist client and Ollama instance (local network or SSH tunnel)","Halist AI client version 1.5+ with Ollama integration support"],"input_types":["text prompts","model selection (from available Ollama models)"],"output_types":["text responses from local models","model availability status (running, stopped, out of memory)"],"categories":["tool-use-integration","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_halist-ai__cap_7","uri":"capability://search.retrieval.conversation.search.and.retrieval.with.full.text.and.semantic.indexing","name":"conversation search and retrieval with full-text and semantic indexing","description":"Halist AI indexes all user conversations using both full-text search (keyword matching) and semantic search (embedding-based similarity) to enable fast retrieval of past conversations. The system builds a searchable index of conversation content, metadata (date, model used), and extracted topics/summaries. Users can search by keywords, natural language queries, or filters (date range, model used, conversation length). Semantic search uses embeddings (likely from a lightweight model like MiniLM or Sentence Transformers) to find conceptually similar conversations even if keywords don't match.","intents":["Quickly find a past conversation about a specific topic without scrolling through hundreds of conversations","Discover related conversations to avoid duplicating work or find previous solutions to similar problems","Filter conversations by metadata (date, model, length) for organization and compliance purposes"],"best_for":["Power users with hundreds or thousands of conversations who need fast retrieval","Researchers and analysts who want to analyze patterns across conversations","Teams sharing conversation repositories who need discovery mechanisms"],"limitations":["Semantic search requires embedding computation, adding ~100-500ms latency per search depending on query length","Index building is computationally expensive for large conversation histories; initial indexing may take minutes to hours","Semantic search quality depends on embedding model quality; domain-specific conversations may have poor results with generic embeddings","No collaborative search or shared conversation indexes—each user has independent search indexes"],"requires":["Halist AI account with at least 10-20 conversations for meaningful search results","Sufficient device storage for search indexes (typically 10-50MB per 1000 conversations)","Optional: GPU acceleration for faster semantic search (CPU-only is slower but functional)"],"input_types":["search query (text, natural language)","filter criteria (date range, model, conversation length, tags)"],"output_types":["ranked list of matching conversations","relevance scores (for semantic search)","snippet previews of matching content"],"categories":["search-retrieval","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_halist-ai__cap_8","uri":"capability://memory.knowledge.conversation.tagging.and.organization.with.custom.metadata","name":"conversation tagging and organization with custom metadata","description":"Halist AI allows users to tag conversations with custom labels (e.g., 'project-x', 'client-feedback', 'research') and organize them into folders or collections. Tags are user-defined and can be applied to multiple conversations, enabling flexible organization without rigid hierarchies. The system supports bulk tagging operations and tag-based filtering in search. Metadata like conversation title, description, and custom fields can be added to conversations for richer organization.","intents":["Organize conversations by project, client, or topic for easy retrieval and team collaboration","Apply consistent metadata to conversations for compliance, billing, or analysis purposes","Create custom views or filters based on tags to focus on relevant conversations"],"best_for":["Teams managing conversations across multiple projects or clients","Professionals in regulated industries who need conversation categorization for compliance","Power users who want fine-grained organization beyond simple folder hierarchies"],"limitations":["No automatic tagging based on conversation content—users must manually tag conversations","Tag management can become unwieldy with hundreds of unique tags; no tag hierarchy or synonyms","Bulk tagging operations are limited to UI-based selection; no API for programmatic tagging","Tags are not shared across users—each user maintains independent tag systems"],"requires":["Halist AI account","Manual effort to define and apply tags to conversations"],"input_types":["tag names (text)","conversation selection (single or bulk)","custom metadata fields (key-value pairs)"],"output_types":["tagged conversation list","tag cloud or tag statistics","filtered views based on tag selection"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_halist-ai__cap_9","uri":"capability://data.processing.analysis.model.performance.analytics.and.cost.tracking","name":"model performance analytics and cost tracking","description":"Halist AI provides analytics dashboards showing per-model performance metrics (response time, token usage, cost) and aggregated usage statistics. The system tracks metrics like average latency per model, total tokens consumed, estimated costs (if using user's own API keys), and success/failure rates. Analytics are computed from conversation metadata and API provider responses, and are displayed in charts and tables. Users can filter analytics by date range, model, or conversation type to understand usage patterns.","intents":["Understand which models are fastest and most cost-effective for different tasks","Track API spending across multiple providers to optimize costs","Identify usage patterns and trends to inform model selection and infrastructure decisions"],"best_for":["Developers and teams evaluating models for production use","Cost-conscious users managing their own API keys","Organizations tracking AI spending for budgeting and compliance"],"limitations":["Analytics are based on Halist's measurements; actual provider billing may differ due to rounding or batching","Cost tracking is approximate if using Halist-managed API keys (users don't see actual provider costs)","No real-time analytics—data is aggregated and updated periodically (e.g., hourly or daily)","Limited drill-down capabilities—can't easily correlate performance with conversation content or complexity"],"requires":["Halist AI account with at least 10-20 conversations for meaningful analytics","Optional: API keys with cost tracking enabled (for accurate cost data)"],"input_types":["conversation metadata (model used, tokens, latency)","API provider responses (token counts, costs)"],"output_types":["performance charts (latency, cost per model)","usage statistics (total tokens, conversations, cost)","comparative analysis (model rankings by speed/cost)"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":43,"verified":false,"data_access_risk":"high","permissions":["Valid API keys for at least one supported model provider (OpenAI, Anthropic, or local Ollama instance)","Network connectivity to model provider APIs or local LLM server","Halist AI account for conversation persistence","Device with sufficient storage for local conversation database (typically <100MB for thousands of conversations)","Operating system with native encryption support (Windows 10+, macOS 10.12+, iOS 13+, Android 9+)","Halist AI client version 2.0+ with local encryption feature enabled","Halist AI account with at least one conversation","Recipient email address or shareable link (for public sharing)","Optional: GPU acceleration for faster summarization (CPU-only is slower)","Halist AI client installed on at least two devices"],"failure_modes":["Response latency increases with multi-model queries due to sequential or parallel API calls to different providers","No built-in cost optimization — users pay per-token to each provider independently without aggregated billing","Model-specific features (e.g., Claude's vision, GPT-4's plugins) may not be fully exposed through the unified interface","Local encryption adds computational overhead (~50-200ms per message depending on key size and device capability)","Cross-device synchronization is limited or disabled in full local mode to prevent encrypted data exposure","Users are responsible for device security — local encryption is only as strong as the device's physical and OS-level security","No server-side backup of encrypted conversations — device loss means conversation loss unless user manually exports","Shared conversations are stored on Halist's servers, requiring trust in Halist's security and privacy","No end-to-end encryption for shared conversations—Halist can theoretically access shared content","Access control is coarse-grained (view/edit/comment); no field-level or response-level permissions","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.36666666666666664,"quality":0.78,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:30.893Z","last_scraped_at":"2026-04-05T13:23:42.552Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=halist-ai","compare_url":"https://unfragile.ai/compare?artifact=halist-ai"}},"signature":"yjF2n3ywv6XAXbhMUBMHMZ4LIvbIZErWcSc30/L0hhoRfJSdO6Hbwuv7yprjok0WMmrPZxsW0Z90XjTgB6ztAg==","signedAt":"2026-06-22T22:27:29.503Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/halist-ai","artifact":"https://unfragile.ai/halist-ai","verify":"https://unfragile.ai/api/v1/verify?slug=halist-ai","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}