In Review

In Progress

Completed

Main Roadmap

Ingest data from Talkwalker

hidden

Ingest data from Nielsen APIs

Ingest Jira tickets

Access Slack data

Read data from Salesforce records

with ability to leverage a known template

Author PowerPoint / Google slides

Social Listening and Web Crawler Tools

Ingest data from Domo Dashboard

Ingest data from WGSN

Ingest data from Ypulse

Ingest content from Google Drive

I’d love to see a more powerful Settings &amp; Preferences page in Storytell that lets users customize how the AI interacts with them and manage what it remembers over time.<h3>What I’m looking for:</h3>1. Personal context A simple “About Me &amp; Company” field to store persistent info like my role, company, focus areas, and common use cases. This would help Storytell give more relevant responses across chats.2. Response preferences Let me define how I want responses to look - tone, format (e.g., bullets vs. paragraphs), level of detail, etc. These preferences should apply by default, not just per chat.3. Memory management Add a clear interface to view, edit, and delete what Storytell remembers — with a master toggle, timestamps, and a “Clear All” option.4. In-chat memory controls I want to be able to say things like “Save: I’m traveling to Japan in June” or ask “What do you remember about me?” and get a clear, visible response.

스토리텔에 더 강력한 설정 및 환경설정 페이지가 추가되어 사용자가 AI와 상호작용하는 방식을 사용자 지정하고 시간이 지남에 따라 기억하는 내용을 관리할 수 있으면 좋겠어요.<h3>제가 원하는 기능</h3>1. 개인적 맥락 내 역할, 회사, 중점 분야, 일반적인 사용 사례와 같은 지속적인 정보를 저장할 수 있는 간단한 '나 및 회사 소개' 필드입니다. 이는 스토리텔이 채팅 전반에서 보다 관련성 높은 답변을 제공하는 데 도움이 될 것입니다.2. 응답 기본 설정 어조, 형식(예: 글머리 기호 대 단락), 세부 수준 등 내가 원하는 응답의 모양을 정의할 수 있습니다. 이러한 기본 설정은 채팅별로만 적용되는 것이 아니라 기본적으로 적용되어야 합니다.3. 메모리 관리 마스터 토글, 타임스탬프, '모두 지우기' 옵션을 통해 스토리텔이 기억하고 있는 내용을 보고, 편집하고, 삭제할 수 있는 명확한 인터페이스를 추가하세요.4. 채팅 내 메모리 컨트롤 "저장해줘요: 6월에 일본 여행 중이에요"라고 말하거나 "나에 대해 기억나는 게 뭐야?"라고 질문하고 명확하고 눈에 보이는 답변을 받고 싶어요.

사용자 지정 설정 및 메모리 컨트롤을 추가하여 스토리텔 경험을 개인화하세요.

Add customizable settings & memory controls to personalize the Storytell experience

We need UI support for three integrations that help with file ingestion and collaboration: Google Drive Integration Allow users to ingest files and folders directly from their Google Drive accounts.<ul><li>A "G Drive" icon will be added to the upload area in the prompt bar.</li><li>Clicking the icon will initiate Google Drive authentication.</li><li>Once authenticated, users can:<ul><li>Select a file → it’s added to the current Collection.</li><li>Select a folder → a sub-collection is created with the same name.</li></ul></li></ul>Slack Integration UI Design and implement a user interface for connecting and managing Slack integration.<ul><li>Allow users to authenticate and link their Slack workspace.</li><li>Surface options for sharing or receiving content via Slack (exact workflows to be defined).</li></ul>Zoom Integration UI Create an interface to support Zoom account linking.<ul><li>Enable users to connect their Zoom account.</li><li>Prepare the UI to support future workflows like ingesting Zoom transcripts or recordings.</li></ul>

Implementing Integrations UI: Google Drive, Slack, and Zoom

Acquisition de données à partir de n'importe quel serveur MCP

모든 MCP 서버에서 데이터 수집

Ingest data from any MCP server

As described here: <a target="_blank" rel="noopener noreferrer nofollow" class="link" href="https://roadmap.storytell.ai/en/help/articles/0396715-predictive-strategic-intelligence-signal-before-you-search">https://roadmap.storytell.ai/en/help/articles/0396715-predictive-strategic-intelligence-signal-before-you-search</a>

Actions: The ability to push signal to people, teams and systems of record

We want to be able to ingest all our Basecamp projects into Storytell

Basecamp (by 37 Signals) Ingest

Looking to replace manual Excel-based tracking with a system that automatically updates project status as new data comes in. Right now, we’re spending time copying over updates that should be dynamically pulled from active work or conversations.The ideal setup would track real-time progress without manual status logs or version control headaches.

Automating Project Tracking Updates

Trying to reduce the manual lift and inconsistency in recurring business reviews by using AI to generate high-quality weekly, monthly, and quarterly reports across multiple clients. The goal is to make the process faster, more reliable, and easier to scale.<h3>What would be valuable:</h3><ul><li>Automatically generate presentations or slide decks from insights</li><li>Export results to CSV or editable formats for further analysis</li><li>Support for large datasets beyond typical row limits</li><li>Enable cross-client comparisons to spot trends across accounts</li><li>Integrate with enterprise tools and meet security/compliance standards</li></ul>It’s especially useful to have the ability to drill deeper into insights, query across multiple datasets, and understand how the system arrived at its answers.

Automate business review reporting across multiple clients

I’m looking to process large volumes of message data (150,000+ messages) to extract structured insights about people and relationships. The goal is to turn messy, unstructured conversations into clean, analyzable data that can power features like:<ul><li>Contact and relationship extraction—Identify people mentioned in messages, extract contact details, and classify relationship types.</li><li>Relationship strength mapping - Categorize connections using a simple 2x2 framework or numeric scale (e.g., weak/strong ties, intimacy scores).</li><li>Interest/topic detection - Surface shared interests and recurring conversation themes.</li><li>LLM-ready formatting - Output the data in a structured format optimized for downstream use by large language models.</li></ul>Ideally, this would include a middleware layer that handles chunking, structuring, and metadata enrichment before sending anything to the LLM, rather than just dumping raw text. That approach would enable scalability (e.g., MapReduce-style processing), maintain context fidelity, and avoid the need for expensive LLM training.This capability would be beneficial for anyone building tools in the relationship management, personal CRM, or social intelligence space, especially when working with high-volume, unstructured message data.If others are tackling something similar, I would love to hear how you approach it.

Extracting relationship intelligence from large message datasets

Ingest Zoom recordings

Bar charts, line charts, pie charts to start.

Render charts & data visualizations in output

I want to be able to load large CSVs into Storytell, and have Storytell query and work with them as part of my internal data knowledgebase.Some CSVs might be 10k or even 100k rows.

Ingest and work with large XLS/CSVs > 10,000 rows

want to bring someone else into the conversation, we expected to be able to just invite them via email right from that thread. Instead, we have to navigate back to the parent collection and share that entire collection with them just so they can access the specific thread we want them to collaborate on.This creates unnecessary friction in our workflow. We often have multiple threads within a collection, and we don't always want to give someone access to everything - sometimes we just want them to collaborate on one specific thread.We'd love to see a feature that lets us invite people via email directly from within a thread. Ideally, this would handle the permissions automatically so that when we invite someone to a thread, they get the appropriate access to participate in that specific conversation without us having to manage the collection-level sharing manually.

email collaboration invitations directly from shared threads

A way to save, reuse, and refine recurring prompts — the Prompt Library would significantly enhance my workflow efficiency.

I want to see my results in a downloadable spreadsheet

We are a market research team that regularly analyzes shopper metrics data. We have a specific use case where we need to compare two CSV files to each other to identify differences and pull together comparative data points.Our current workflow involves looking at a lot of data comparatively, and we often need to tell year-over-year stories by comparing target audience data to control groups. We have CSV files containing shopper metrics data that we need to analyze, including calculations and breakdowns that we would like our tool to pull together automatically.We understand that the tool may not have granular snapshot capability yet, but we're hoping that with its current capability, we can compare target audience data to control data more efficiently. Currently, this process is quite manual and time-consuming.We attempted to work with the current system by converting CSVs to XML format to perform the analysis, but we're looking for a more streamlined approach that can handle CSV comparison natively.Our ideal outcome would be to upload two CSV files and have the system automatically identify key differences, patterns, and provide comparative insights without requiring manual data transformation.

Compare two (or more) CSV files

We've noticed that when clicking on a prompt suggestion in our interface, it inputs the prompt text but still requires us to manually click the 'Send' button to execute it. This feels like an unnecessary extra step in our workflow.Currently our experience is:<ol><li>Click on a prompt suggestion</li><li>Prompt text gets filled in</li><li>We still need to click 'Send' to actually run the prompt</li></ol>We'd prefer if clicking a prompt suggestion would automatically execute it, eliminating the need for the additional Send button click. This would streamline our user experience and make the prompt suggestions feel more immediate and responsive.

Auto-send prompt suggestions instead of requiring manual Send button click

I’m working on a project to analyze a large volume of customer call transcripts and automatically surface patterns and insights. My goal is to move away from manual review and instead use Storytell to detect recurring issues, feature requests, and emerging opportunities across our client base. To do this effectively, I need a way to ingest transcripts at scale and automatically summarize key trends. The output should help us quickly identify what matters most to our users without manually combing through every call.

Analyzing Customer Call Transcripts to Identify Trends

We want to start with sharing just what we've highlighted from our content analysis work.<ul><li> Content Selection We need users to be able to pick exactly what they want to share from their highlighted content, rather than sharing everything at once.</li><li>Curation and Permission Settings Once content is selected, users should be able to edit and curate that content block. This includes setting interaction permissions:</li></ul><ul><li>Anyone with the link can interact</li><li>Anyone at our company can interact</li><li>Specific people only</li></ul>An important note: when users make edits during this curation process, we want those human improvements to feed back into our algorithm for better future recommendations.We've noticed that we're already doing a manual version of this workflow when we share curated insights in our team channels - this feature would automate and enhance that natural sharing behavior.