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    mfigueroacontreraNew Participant

    Unified Bot with Intelligent Mode Selection (Search vs AI Assistant)1. New

    InspirationApple Siri AI announcement (June 2026) introduces automatic mode detection for user queries. Simple searches default to Spotlight search results; complex requests route to LLM-powered explanations. This pattern creates a seamless unified experience without user friction or explicit mode selection.Problem StatementUsers interacting with Moveworks currently experience cognitive load when determining whether they need quick search results or deeper AI-assisted reasoning. This split mental model across different bot capabilities or interfaces reduces perceived simplicity and increases support friction for end-users.Proposed SolutionMoveworks implements a unified bot interface with intelligent query routing:Single entry point: Users always interact with one Moveworks bot.Automatic mode detection: The bot analyzes incoming queries and determines the optimal response pathway.Response modes:Enterprise Search mode (simple/direct queries): Returns curated knowledge base results, IT catalog items, HR policy documents, or employee directory records with minimal latency and maximum precision. AI Assistant mode (complex/nuanced queries): Leverages LLM reasoning for contextual analysis, multi-step guidance, or explanatory responses that benefit from natural language generation.No friction: Users do not select a mode or mode type. The bot makes this determination transparently.Business ValueUnified experience: Single bot builds user confidence and reduces learning curve across the organization. Reduced support load: Lightweight queries get fast answers without LLM overhead. Complex queries benefit from AI reasoning without forcing structured search workflows. Improved adoption: Employees default to the bot as a reliable all-in-one agent rather than navigating separate search tools or AI assistants. Operational efficiency: Query routing optimizes cost and latency by matching query complexity to appropriate infrastructure.Technical ConsiderationsClassification logic: Implement lightweight pre-processing to categorize queries (intent detection, keyword heuristics, query length, entity recognition). Avoid excessive latency overhead. Fallback behavior: Define graceful escalation if classification is ambiguous. Analytics: Track mode distribution, user satisfaction by mode, and accuracy of routing decisions to refine classification thresholds over time. Transparency (optional): Consider subtle UI affordance (e.g., "Search results" vs "AI insights" label) to help users understand why they received a particular response type without forcing explicit selection.Competitive PositioningApple Siri AI demonstrates this pattern as table stakes for modern AI assistants. Moveworks adopting this approach positions the platform as intuitive and frictionless, matching user expectations set by consumer AI products while maintaining enterprise-grade knowledge integration.

    afleury
    afleuryInspiring

    Adaptive Cards – Multi-line Textbox Usability (Web Assistant)1. New

    SummaryMulti-line textbox (Description field) in Web Assistant adaptive cards cannot be resized. Impacts usability vs expected behaviour in modern web forms. Problem StatementUsers cannot expand the Description field. Limits visibility of typed content. Creates friction when entering longer responses. Behaviour differs from other experiences (e.g. Teams variant handled separately but has the same issue). Current BehaviourFixed-size textbox in Web Assistant adaptive cards. No drag-to-resize or auto-expand capability. Expected BehaviourTextbox supports: Manual resize (drag handle) Auto-expand based on content length Scroll fallback only after max height reached ImpactReduced user experience in Moveworks portal flows. Slower form completion for Service Desk requests. Increased risk of truncated or poorly formatted input.Business ContextUsed in bot-fillable forms via Moveworks → ServiceNow integration. Affects high-volume request scenarios (e.g. Ad Hoc Request forms).Proposed SolutionEnhance adaptive card rendering in Web Assistant: Enable dynamic height for multi-line text inputs Add optional config flag for “resizable = true” Maintain parity with Teams or other supported channels where applicable Alternatives ConsideredNone viable currently (confirmed by Engineering as enhancement only). Success CriteriaUsers can comfortably enter long-form text without UI constraints. Improved completion speed and quality of inputs. Reduced agent follow-up due to incomplete descriptions.Current​​​​​​Future State - What it could look like 

    afleury
    afleuryInspiring

    Support Locale-Specific Date Formatting in In-Bot Fillable Forms1. New

    SummaryMoveworks in-bot fillable forms currently default to US date format (MM-DD-YYYY) and do not respect user or tenant locale settings such as en-AU (DD-MM-YYYY).ProblemDates appear in US format regardless of regional settings Creates ambiguity (e.g. 04/08/2026) for AU/NZ users Issue is consistent across MS Teams and Web AI Assistant ServiceNow correctly honours locale, highlighting inconsistencyExample below, date is in US format. Investigation OutcomeConfirmed by Moveworks Support and Engineering No configuration option to control date format Behaviour likely tied to rendering layer, not user settings No workaround available todayImpactConfusing user experience Risk of incorrect date submission Additional validation effort for Service Desk Reduced trust in bot-driven request accuracyRequestIntroduce support for locale-aware date formatting in in-bot forms, including:Automatic detection of user locale (preferred) Tenant-level locale override Optional field-level format control (DD-MM-YYYY, MM-DD-YYYY, etc.) Consistent behaviour across Teams, Web, and other platformsPriorityMedium–HighAdditional ContextThis is a basic expectation for global organisations. Lack of locale support is a gap for AU deployments and limits adoption of in-bot forms.Expected OutcomeDates displayed and submitted in Moveworks forms align with user regional settings, removing ambiguity and improving accuracy.