Overview This release delivers significant stability improvements across xdge, an upgraded notification system, smoother workflows, improved meeting reliability, and UI refinements across all screen sizes. We worked with key issues impacting Clips, workflows, and meeting bots, while introducing enhancements that make xdge faster, clearer, and more intuitive to use.
đ New Features
Enhanced Notification System
Real-Time Bell Notifications
Stay on top of activity without checking multiple places. The new in-app notification center provides clearer, faster alerts:
Critical system events now appear instantly in the bell icon
Team activity notifications keep you updated on workspace actions
Redesigned formatting makes every notification easier to read
Trial Expiration Email Alerts
Workspace admins now automatically receive an email when a 14-day trial expires, ensuring complete visibility into subscription status and next steps.
⨠Improved User Experience
Automatic Clip Access
Once a Clip recording is complete, xdge now:
Opens a new tab automatically
Navigates directly to the newly created Clip No more hunting for your recording â youâre taken straight to your content.
Across many IT and operations teams, there is a recurring moment at the end of each month when the momentum of day-to-day work pauses and gives way to a very different class of obligation, not a technical outage, not a crisis demanding immediate resolution, but the slow and persistent burden of assembling the month-end report. What begins as an apparently simple requirement to consolidate weekly activity logs quickly mutates into a time-consuming exercise: hunting down the correct versions of spreadsheets, reconciling columns that do not perfectly match, filtering out anomalies that quietly creep into the data, constructing pivot tables with precisely the layout leadership expects, and finally shaping the results into something polished enough to present. It is a process so deeply entrenched in organizational routine that teams no longer question its existence; they perform it because it has always been done, not because it has ever been efficient.
The tension at the heart of this ritual is the mismatch between its significance and its mechanics. Reporting is essential for understanding operational health and performance, yet most of the effort required to produce it is mechanical rather than analytical. As organizations expand, adding more departments, projects, initiatives, and layers of activity, the volume of data grows, but the reporting method remains trapped in a fixed, manually driven paradigm. The result is a system that scales in workload but not in intelligence. Teams spend more hours performing the same low-leverage tasks without producing additional insight; the friction increases, but the value does not.
You can see the structural flaw most clearly when leadership asks what seems like a harmless follow-up question: âCan we break this down by team?â or âCan we show projects separately?â or âCan we isolate incidents from project work?â What appears to be a request for a simple alternate view often requires a complete dataset rebuild, triggering a cascade of redundant labor. Manual reporting, by its nature, locks teams into a backward-looking, fragile workflow. It forces analysts to invest their highest-quality cognitive effort not in interpreting what the data means, but in assembling, cleaning, and normalizing the data just so it can be interpreted later. It fosters accuracy but discourages curiosity. It redirects technical leadership away from strategy and toward clerical cleanup.
Automation breaks this pattern not simply by accelerating the process, but by fundamentally altering its structure. When built correctly, an automated reporting pipeline replaces improvisation with determinism. It eliminates whole classes of errors that manual workflows inevitably produce, such as schema drift, inconsistent labeling, misaligned ranges, accidental omissions, and restores clarity to a process that has slowly accumulated complexity through years of minor ad-hoc adjustments. Once the mechanical layer disappears, teams are free to focus on the interpretive and strategic insights that reporting was always meant to support.
To understand the extent of this transformation, it helps to examine how a well-designed, AI-driven reporting workflow operates when engineered from first principles.
How the Automated Workflow Works
We designed the workflow as a sequence of logical, dependable stages, each one intentionally removing a category of manual effort that previously consumed hours of attention and introduced a wide range of failure modes.
1. Data Gathering from Source Files
The process begins with automated source discovery: the system searches a designated repository, such as Google Drive, for the weekly Excel files that make up the month's activity (e.g., âAugust Week 5 Tasksâ). Instead of relying on humans to find and open the correct files, the workflow performs deterministic file matching, followed by schema validation that ensures all expected fields, Business Unit, Department, IT Group, Project Code, Priority, Status, and others, are present and correctly named. This prevents silent inconsistencies, ensuring the workflow operates only on structurally sound inputs.
2. Extraction and Consolidation
Once validated, the files are ingested into the system, which extracts the relevant fields and consolidates them into a single unified dataset. During this step, the workflow applies cleansing rules that remove empty rows, zero-value entries, malformed records, and error states. It performs type consistency checks, deduplication, and column-order normalization, so downstream analysis runs on a clean, coherent foundation. What typically requires manual copying, filtering, and reformatting is completed deterministically in seconds, producing a dataset free from structural anomalies.
3. Automated Summary Tables
With the master dataset established, the system generates several structured summaries that present the data from different analytical angles:
By Business Unit: showing the distribution of IT effort across organizational domains like Finance, Operations, and Customer Service.
By Department / Team: revealing the internal allocation of resources across functional groups.
By Activity Type: breaking work into meaningful categories such as project tasks, support, maintenance, training, and compliance. A semantic normalization layer resolves inconsistent naming, treating âProject Work,â âProjects,â and âProj Workâ as the same category, ensuring accuracy even when individual contributors use different labels.
IT Group Workload: summarizing hours by IT group and by individual, highlighting capacity load, bottlenecks, and utilization imbalances.
These tables, which typically require a full day or two of pivoting and re-pivoting, are now generated automatically and consistently.
4. Project Portfolio Analysis
The workflow then analyzes the project landscape in greater depth. It groups projects by status (Completed, In Progress, Pending), ranks the top 10 by hours invested, and calculates indicators such as completion rates or approximate progress positioning. This provides a transparent view of where the monthâs project time went and whether high-effort initiatives are progressing proportionally.
5. KPI Calculations
Beyond simple rollups, the system computes key performance indicators that convert raw logs into operational signals: project-to-BAU ratios, incident percentages, category averages, team capacity utilization, and time-series variance metrics. These KPIs allow leadership to see whether the organization is moving toward more strategic work or being pulled back into reactive tasks.
6. AI-Generated Insights and Recommendations
After constructing the numerical scaffolding, the system moves into interpretation. It identifies anomalies, detects emerging patterns, and produces narrative insights that would typically require an analystâs attention and judgment. If, for example, one business unit shows an unexpected surge in support hours, the AI highlights it and may infer likely drivers. If incident load becomes disproportionately high relative to previous months, it may suggest opportunities for automation or problem-management interventions. These insights turn the report into a strategic asset rather than a passive summary.
7. Professional Report & Delivery
Finally, the workflow compiles all tables, visualizations, KPIs, and insights into a well-structured, executive-ready document. It presents the information in a consistent, readable format, Business Unit Distribution, Activity Analysis, Top Projects, KPIs, Strategic Recommendations, and automatically saves the report to shared storage, optionally posting a digest to Slack. No manual formatting, exporting, or stitching together of multiple documents is required. Everything is produced in one automated pass.
Each of these steps runs in the background with a single trigger, requiring no supervision, no manual adjustments, and no reassembly of spreadsheets when leadership requests another slice of the data.
The Broader Impact of Automation
The broader significance of this approach is that it does more than eliminate repetitive work; it reframes how organizations understand their operational reality. When the burden of cleaning, merging, and validating data disappears, teams can focus on interpreting patterns, why one groupâs workload increased, why a particular category of incidents spiked, which projects are consuming disproportionate time, where capacity is strained, and where efficiencies can be introduced. Insights that were once buried beneath hours of clerical work now surface naturally as part of the workflow.
For organizations that have relied on manual reporting for years, the improvement feels almost disproportionate to the change in process. What once demanded an entire afternoon now completes itself in the background, quietly and reliably. The immediate gains are time savings and reduced cognitive load, but the long-term impact is the return of analytical clarity: the ability to think strategically rather than mechanically.
This release introduces a fully unified notification center, major improvements to workflow reliability, faster Slack activity search powered by OpenSearch, and a cleaner trial/onboarding experience. We focused on strengthening platform stability, improving meeting and workflow performance, and elevating the UI across every touchpoint. With dozens of fixes and refinements, this release significantly streamlines how users navigate, search, collaborate, and automate their daily tasks.
đ New Features
14-Day Trial Expiry Notifications
You now receive clear email notifications when your 14-day trial ends. Messaging is correctly routed only to workspace owners, eliminating confusion for team members. The updated emails provide clarity on workspace status, renewal options, and next steps.
OpenSearch-Powered Slack Activity Search
Slack activity search is now dramatically faster. Fetch times have been reduced from nearly one hour to under 30 seconds, enabling more reliable workflows, usage analysis, and report generation.
Clips Permission Alerts
Clips now detects when camera or microphone permissions are blocked and surfaces an immediate warning dialog. This helps users resolve recording issues proactively and prevents silent failures during clip creation.
đ ď¸ Major Improvements
Unified Notification Experience
The bell icon now displays workflow reports, deep research updates, shared clips and meetings, team activity, collections alerts, and system notifications all in one place. Outdated notifications have been removed, ensuring users see only timely, relevant activity.
AI Transparency in Result Limitations
The AI now notifies users when a tool returns capped or partial results. This provides clearer expectations, reduces confusion, and improves trust in data completeness.
đ Bug Fixes
Meetings & Communication
Scheduled Zoom meetings now appear consistently in the Upcoming Meetings tab
Only one bot joins Google Meet, resolving duplicate-bot issues
Meeting pages now use standardized spacing and font styles
Onboarding & Trial Experience
Trial expiry emails now route to the correct recipients
The upgrade modalâs close button behaves reliably
Trial expiry pop-up has improved icons, spacing, and readable action buttons
The sign-up screen now has refined spacing, colors, and imagery
Search
Search no longer stalls after onboarding or connector setup
Calendar and Gmail-linked search scenarios now return consistent results
Workflows
Duplicate workflow notifications are eliminated
Salesforce workflow code generation is now reliable
Jira workflow reports no longer get stuck on âFetching detailsâ
Workflow duplication errors have been fully resolved
Newly created workflows and workflow reports appear instantly without refresh
Slack workflow reports now show proper user names, not raw IDs
Workflow scheduler time dropdown renders correctly across all screen sizes
Deep Research
Deep research reports now complete consistently without errors
Assistant failures in QA environments have been resolved
Clips
Optimized thumbnails that now show a proper placeholder
Search results use the correct icon instead of default or incorrect logos
Clip timestamps now display in local timezone (UTC)
User Interface
Follow-up queries are visually centered
Email templates now have consistent branding, spacing, and readable formatting
Slack Integration
Slack bot messages produce properly aligned bullet points
⥠Performance Enhancements
Query & Workflow Stability
Workflow tiles and workflow reports now appear immediately after generation
Search and Assist performance has improved, especially after new connector onboarding
Internal routing and display pipelines are more responsive across the UI
Monitoring Upgrades
Additional logging and visibility have been added for search and workflow performance diagnostics
đ Security Updates
Access Control Improvements
Trial-related modals and system notifications now respect updated admin-only visibility
Authentication issues with Slack bot automations have been fixed
Token handling across automated workflows is now more secure
𧚠Deprecations & Removals
Legacy Notification Behavior
Outdated, older notifications are no longer shown in the bell center
Redundant or stale system prompts have been removed for clarity
đ§ Infrastructure & Operations
System Stability Improvements
Build stability has improved across frontend pipelines
Logging for trial expiration, workflow creation, and Slack activity retrieval has been expanded
Automation reliability has been strengthened for on-call jobs and background workers
We're excited to share the newest updates to your platform. This release introduces powerful real-time Web Search, expanded Google Apps write capabilities, enhanced GoLinks, and major improvements across Assist, Search, and Workflow management.
This release brings significant advancements to help your teams research faster, automate more confidently, and collaborate more effectively:
Web Search across the entire platform
Verified Google Calendar, Drive, and Gmail write scopes
Streamlined workspace creation for sales and growth teams
More reliable GoLinks and Assist responses
Faster, more accurate Slack search and reference handling
đ New Features
Web Search & External Search
Real-Time Web Research Across the Platform
Bring the power of the internet into your workflows, deep research, and Assist queries, seamlessly blended with your internal workspace data.
What's included:
Direct web search inside Assist, Deep Research, and Workflows
Intelligent source filtering between apps, collections, files, and the web
Proper formatted references and source attributions
Time-based filtering for the most current results
Required Action: Enable Web Search in your workspace settings, then use it in Assist or Workflows to expand your research beyond internal knowledge.
Integration Enhancements
Google App Verification & Write Scopes
Weâve added verified support for Google Calendar, Drive, and Gmail write scopes, unlocking deeper, more powerful automation.
Capabilities:
Create and update calendar events
Write to Drive folders and files
Send emails and automate Gmail actions
Required Action: Reconnect your Google account to enable new write-level permissions.
Workspace Management
Streamlined Workspace Creation for Sales Teams
Sales and growth teams can now spin up new prospect workspaces instantly, without requiring manual onboarding from prospects.
Whatâs new:
Direct workspace creation
Automatic Pro trial activation
Proper admin assignments during setup
Required Action: Use the Workspace Creation panel to set up new trial environments for prospects in just a few seconds.
đ Major Improvements
GoLinks Enhancements
Smoother, Smarter Link Management
GoLinks now offers a more intuitive editing and sharing experience.
Improvements:
Edit modals pre-fill with existing link data
Accurate sharing of feedback while creating or editing
Clear duplicate prevention with actionable messaging
Sharing status displays correctly throughout the process
Assist Experience
More Intelligent and Reliable Responses
Assist now responds with more accuracy and cleaner formatting.
Updates:
App-specific filtering now correctly limits the response sources
Eliminated JSON formatting glitches
Restored proper formatting for reasoning steps
Search & Discovery
Faster, More Accurate Information Retrieval
Search and discovery across your workspace just became significantly more reliable.
Enhancements:
Better semantic Slack search, including threaded conversations
Eliminated UI overlap and animation issues
Cleaned and consistent reference formatting for Slack messages
đ Bug Fixes
User Interface
Fixed dropdown text overflow when multiple apps/collections are selected
Resolved notification dot appearing incorrectly during time filter selection
Corrected font inconsistencies in web search buttons
Addressed search tab animation glitches
Data Access & Sharing
Fixed âAccess Deniedâ errors when chatting with shared reports
When teams start working seriously with AI, familiar patterns emerge.
One prompt gets written to generate product copy. Another way to summarize feedback. Another way to rewrite a brief. Soon, these prompts are scattered, shared in Slack threads, buried in Notion, stashed in Apple Notes. People tweak them, lose track of them, and forget where the best version lives.
And as your team leans on AI more, the gap becomes obvious.
Because what youâre building isnât just a collection of prompts. Itâs a body of skills.
We call it the Skills Library because itâs about more than storing prompts; itâs about turning them into durable, reusable knowledge.
A single prompt might be a sentence in a textbox, a clever experiment, or a helpful shortcut. But when that prompt gets refined, reused, and shared across a team, it becomes something more. It becomes a repeatable process. A standard. A skill.
The Skills Library is where this evolution occurs, where prompts evolve into structured, versioned, team-ready tools. Like code or design systems, they stop being one-off inputs and become part of how your organization actually works.
Why We Built It
A good prompt doesnât just work once; it becomes part of how your team gets work done. You refine it over time, adapt it to different inputs, and reach for it again when the same task comes up. Eventually, it becomes something worth sharing, not just because it saves time, but because it consistently outperforms a blank page.
The problem is that most teams store these in the wrong places. Note apps, Slack threads, and Notion pages are none of them built for structured reuse. They donât version your work, they donât support execution, and they donât let others build on what you've already figured out.
The Skills Library changes that. It gives teams a way to manage AI logic like tangible operational assets, searchable, shareable, versioned, and ready to run. What starts as a well-crafted prompt becomes something much more: a reusable, living component in the way your team works.
What Lives in the Skills Library
AI-native work tends to organize itself around a few recurring formats. Weâve formalized those into four types of skills:
Prompts These are lightweight, flexible inputs, often with placeholders. Theyâre ideal for tasks that vary slightly each time but follow a familiar structure. For example: âWrite a note to [Name] summarizing [Project] for [Quarter].â
Workflows More rigid and repeatable. Workflows are designed for consistencyârun the same way every time, often on a schedule. They're perfect for tasks like daily digests, weekly summaries, or standardized reports.
Agents These are predefined AI behaviors with a distinct tone, knowledge base, or style but without a specific task until runtime. Think of them as experts waiting for direction. You donât have to tell them how to work, just what to work on.
Tasks These go beyond generating text. They perform actionsâcreate a document, update a Jira ticket, send an email. They bridge the gap between language and execution, automating the steps that typically follow a prompt.
Templates for each of these types are available out of the box, certified by xdge AI and built for everyday use cases. But the real power comes when your team starts building its own: evolving internal knowledge into a library of living, executable tools.
From Knowledge to Interface
Whatâs powerful about the Skills Library isnât just what it stores, itâs how it works.
It turns knowledge into UI.
You can search by department, tag by use case, or browse by category. You can click to preview, click to edit, and click to run. The same way IT teams manage software rules, or data teams manage queries, AI-native teams can now manage real, executable work.
Need a prompt for summarizing churn feedback? Search â Select â Run.
Want to schedule a workflow that generates weekly product updates? Tag it â Schedule it â Done.
Sharing a marketing agent with a new team member? Copy the link and everythingâs preconfigured.
This is how prompts become usable infrastructure. Youâre not only storing ideas, youâre deploying them.
At first glance, the Skills Library might look like a utility, a more innovative way to organize prompts and workflows.
But in practice, it becomes infrastructure. It helps teams scale their use of AI not through experimentation alone, but through repeatable systems that improve over time. A good prompt doesnât stay in one personâs notes. It becomes a skill that the entire team can use and build on.
Out of the box, the Skills Library includes templates for various everyday tasks, including research, content generation, analysis, triage, and more. However, over time, your team develops its own stack, a set of living, evolving tools that reflect the way you work.
The Knowledge Layer Teams Rely On
As AI embeds itself deeper into work, a new layer is forming, one that sits above your data and above your tools. This is the knowledge layer: the part of the system that encodes how work gets done.
The Skills Library is the interface to that layer. It turns tacit know-how into something searchable, executable, and reliable.
Most teams wonât describe it this way. Theyâll just notice work moving faster. Fewer things slip through the cracks. Good ideas spread. The same task takes half the time.
Thatâs what it looks like when knowledge becomes a system, work stops being reinvented, and simply gets done.
Certified Skills, at Scale
The Skills Library isnât just a tool, itâs a growing ecosystem. Weâre launching with dozens of certified Skills available today, and soon there will be hundreds more. Each one is reviewed and standardized by xdge AI so teams can trust what theyâre using. Whether itâs release notes, sales outreach, invoice workflows, or call summaries, Skills come pre-built, certified, and ready to apply across the org.
If youâre a knowledge worker, a manager, or really just anyone trying to keep your head above water with technology right now, you probably know this feeling. The workplace is flooded with single-purpose AI tools. They each promise to revolutionize productivity, but they donât really connect. Instead, you end up with fragmentation, not efficiency.
Thatâs why we built xdge. Itâs spelled X D-GE, but pronounced âedgeââas in having a competitive edge. That name reflects our mission: to unify knowledge and automation so every employee can stay productive, connected, and focused on what matters most.
Our Mission: Productivity First
From the very beginning, we designed xdge with a strong B2B focus. This isnât consumer AI bolted onto business softwareâitâs purpose-built to connect employees directly to company knowledge, the tools they use every day, and the automated workflows that keep work moving.
Our vision follows four stages:
Search â making scattered information instantly accessible.
Knowledge Management â organizing it into something coherent and usable.
Workflows and Automation â enabling people to act intelligently with that knowledge.
Productivity â delivering measurable results across the organization.
A Toolkit That Works Where You Work
We designed xdge to feel less like a single tool and more like an operating system for knowledge work. That means meeting employees where they already areânot forcing them into another dashboard.
With meeting bots, clips for capturing audio, video, and screen shares, Go links for fast navigation, Slack integrations, browser extensions, curated knowledge collections, and unified search and chat across all apps, xdge captures and connects knowledge wherever it happens, in any format.
To lower the barrier even further, we created pre-packaged departmental solutions that work right out of the box: pipeline analysis for sales, inbox zero automation for email, Jira compliance for engineering, Slack recaps, and even auto-generated daily to-do lists.
Statefulness: Going Beyond Stateless Automation
At the core of xdge is the way we merge knowledge and automation. Traditional automation platforms are statelessâthey run a script and forget. We built xdge workflows to be stateful. They draw from organizational knowledge before making a move.
For example, instead of sending a canned reply to an incoming email, xdge can check if the sender is on your calendar, review the project status in Jira, confirm billing history, and then craft a smarter, more relevant response. Itâs a leap from rigid, one-size-fits-all automation to context-aware decision-making.
Workflows Built for Simplicity, Intelligence, and Trust
We made workflows simple enough to build in natural languageâno flowcharts or coding required. To expand flexibility, we introduced Vibe Coding, which lets the AI generate tools on the fly within safe, pre-authorized boundaries. And with Safe Mode, you always see exactly what a workflow will do before it runs. That way, automation is powerful, but oversight stays firmly in human hands.
Competing Across the Landscape
We know the market is crowded. Thatâs why we deliberately designed xdge to close the gaps left by four categories of tools:
Enterprise knowledge platforms like Glean or Copilot are strong in search, but we go further by pairing bots, clips, and a hybrid API + crawl retrieval approach that delivers fresher data at lower cost.
Automation platforms like Zapier or Workato provide orchestration, but theyâre stateless and developer-heavy. xdge matches that depth while making workflow creation accessible in natural language, powered by stateful knowledge.
B2C AI assistants like ChatGPT Enterprise are generalists. We built xdge enterprise-first, with certified, auditable workflows that connect directly into business systems.
Specialized point solutions may shine in one task but donât talk to each other. xdge eliminates that overhead by giving you one connected platform.
Engineering for Cost Efficiency
Power only matters if it scales affordably. Thatâs why we engineered xdge to be 2â3x more cost-efficient than alternatives like ChatGPT Teams.
Our hybrid API + crawl retrieval indexes what mattersâstructured data via APIs in real time, and static content through scheduled crawls. This dramatically reduces infrastructure costs. On top of that, xdge is LLM-agnostic, dynamically choosing the right model for each step of a workflow, balancing cost, speed, and performance.
The Bigger Picture
Our pitch is simple: unify search, knowledge, workflows, and automation into one cohesive platform thatâs safe, scalable, user-friendly, and cost-effective.
We built xdge to replace the fragmentation of dozens of disconnected apps with a single system that captures, organizes, automates, and delivers measurable productivity.
The question for enterprises isnât whether fragmentation is costlyâwe all know it is. The question is: will you unify?
We're excited to share the latest updates to your platform. This release introduces groundbreaking capabilities in Workflow automation, a comprehensive Skills Library, enhanced recording features, and numerous improvements based on your feedback.
This release brings significant advancements to help you work more efficiently and effectively:
Skills Library Launch: Access a comprehensive collection of prompts, workflows, and templates organized by department
Next-Generation Workflows: Execute actions beyond analysis, including integration with Salesforce, JIRA, and email systems
Workflowâs Enterprise Safe Mode: Test workflow actions safely before production execution
đ New Features
Skills Management
Skills Library Launch
Browse and discover prompts, workflows, agents, and tasks in our new comprehensive Skills Library. The library is organized by department and author, making it easy to find relevant templates and best practices from across your organization.
What's included:
6+ ready-to-use workflow templates
Dedicated skills website for easy access
Department-based organization
Author attribution and sharing
Required Action: Access the Skills Library from the main navigation to explore available templates and start using them in your workflows.
Workflow Automation
Next-Generation Workflows with Actions
Workflows now go far beyond analysis - they can actively execute tasks in your enterprise systems. Label Salesforce opportunities, flag policy violations in JIRA, classify emails, and more, all through intelligent workflow automation.
Key capabilities:
Direct integration with business systems
Automated task execution
AI-driven decision making
Seamless data flow between applications
Required Action: Create action-enabled workflows using the new workflow builder. Start with Safe Mode to test functionality before full deployment.
Workflow Security
Safe Mode for Enterprise Workflows
Mitigate risk with our new Safe Mode feature that generates preview reports of all actions before execution. Validate outcomes and ensure workflows perform as expected before committing changes to your production systems.
Benefits:
Risk reduction through preview validation
Confidence in automated actions
Enterprise-grade safety controls
Preserved workflow plans between test runs
Required Action: Enable Safe Mode in the workflow creation modal when building new workflows to test them thoroughly before production use.
Tool Generation
Automatic Tool Creation
The platform now dynamically generates new tools through AI-driven code synthesis, extending your enterprise systems on demand without waiting for vendor API updates or custom development.
Capabilities:
Custom tool generation for specific use cases
Automatic instrumentation creation
Breaking free from API limitations
On-demand system extensions
đ Bug Fixes
Recording & Playback
Recording and Playback Issues Resolved
Fixed video playback problems on various devices
Resolved audio/video synchronization issues
Corrected distorted visuals during recorded video playback
Fixed audio-only recording playback issues
Search & Discovery
Search and Assist Fixes
Restored confidence scores in AI-generated responses
Fixed missing references and citations in search results
Resolved app connector and filter issues
Improved search result accuracy and reliability
User Interface
Navigation and Interface Fixes
Fixed overlapping issues between go-link auto suggestion and search filters
This release introduces Clips, our revolutionary new screen recording and meeting capture tool, alongside significant enhancements to search functionality, meeting integrations, and the overall user experience across the platform. We've resolved critical bugs in search citations, enhanced browser compatibility, and streamlined our infrastructure for better performance. This update focuses heavily on delivering a polished, production-ready Clips experience while maintaining reliability across all core platform features.
