# Emolysis > Emolysis is the agentic lakehouse for data engineering and analytics. Direct a team of agents from your laptop to investigate business questions, develop dashboards, and build and test pipelines for your data platform. An entire data team. One download. Made by Bandpey GmbH. Underneath is a local-first coding agent: it picks one of ten pipeline shapes, fills a template written for your platform, proves it with golden tests on DuckDB on your machine, and only then deploys it to Databricks, with Snowflake and Microsoft Fabric planned. Status: in private development; early access by invitation; nothing is released yet. Website: https://emolysis.com/. Short index of pages: https://emolysis.com/llms.txt. ## Status Emolysis is in private development, and early access is by invitation. Nothing is released yet: there is no download, no public release and no release date. Accounts open with early access. The website describes Emolysis in the present tense, as the product it is; this status applies to all of it, and platform statuses (in development, planned) apply to each platform. The sample dashboard on the website renders the same chart specs the agent produces, on synthetic data. ## About Emolysis Emolysis is the agentic lakehouse for data engineering and analytics, a product of Bandpey GmbH in Munich, Germany. Emolysis puts a team of agents at your direction from your laptop: to investigate business questions, develop dashboards, and build and test pipelines for your data platform. Underneath is a local-first coding agent that builds data pipelines from tested templates for ten pipeline shapes, proves them with golden tests on DuckDB on your machine and deploys them to Databricks, with Snowflake and Microsoft Fabric planned, and turns a business question into a gold table and a shared dashboard. Status: in private development; nothing is released yet. About page: https://emolysis.com/about. ## Company: Bandpey GmbH Bandpey GmbH is a German data and AI services company in Munich. It works with enterprises in retail, telecommunications, energy, financial services, manufacturing and pharma, from data infrastructure and platform architecture to data science, MLOps and generative AI, and it makes Emolysis. Its co-founder and CEO is Roozbeh Bandpey. Website: https://bandpey.com. - Address: Gmunder Str. 20b, 81379 Munich, Germany. - Register: Amtsgericht München (Munich Local Court), HRB 285782. - Imprint: https://emolysis.com/legal/imprint. ## Founder: Roozbeh Bandpey Roozbeh Bandpey is an entrepreneur and AI engineer based in Munich, with more than 20 years of hands-on software engineering. He is the co-founder and CEO of Bandpey GmbH, the company that makes Emolysis, and its managing director. Bandpey is a German data and AI services company. It works with enterprises in retail, telecommunications, energy, financial services, manufacturing and pharma, on everything from data infrastructure and platform architecture to data science, MLOps and generative AI. Emolysis, the agentic lakehouse for data engineering and analytics, comes out of that work, and Roozbeh is building it. It is in private development, and nothing is released yet. His career runs through data platforms and machine learning in production. At Accenture he was a Distinguished Engineer and Head of Data and MLOps for Germany, Austria and Switzerland, and he founded the firm's Databricks Center of Excellence. Before Accenture he led machine learning deliveries at Reply, worked on natural language generation for a voice assistant at Samsung Electronics, and did research at the University of Stuttgart and at Robert Bosch GmbH. He has been a Databricks Solutions Architect Champion, an invitation-only program, since November 2021. Since September 2026 he is also the founder and CEO of FACTHORY, an AI-native operating system for industrial work. He writes about generative AI, AI agents, GPUs, AI infrastructure, cloud and distributed systems. Career, newest first: - Since 2026, FACTHORY: Founder and CEO. An AI-native operating system for industrial work, founded in September 2026. - Since 2023, Bandpey GmbH: Co-founder and CEO. A German data and AI services company in Munich, working with enterprises from data infrastructure and platform architecture to data science, MLOps and generative AI. Since June 2023. Bandpey makes Emolysis, the agentic lakehouse for data engineering and analytics. - Since 2021, Databricks: Solutions Architect Champion. An invitation-only program for solutions architects, since November 2021. - 2021 to 2023, Accenture: Distinguished Engineer, Head of Data and MLOps for Germany, Austria and Switzerland. Databricks partner lead for EMEA strategic alliances. He founded Accenture's Databricks Center of Excellence, was the first Databricks Champion in Accenture EMEA, trained and certified more than 100 professionals, and led the work behind Accenture's 2023 Databricks Partner of the Year award. Before that, as Engineering Manager for Data and AI, he led MLOps and data and ML platform work for insurance clients. - 2019 to 2021, Reply: Technical Team Lead and Lead Machine Learning Engineer. Led machine learning deliveries: MLOps, microservices on Kubernetes, and ML pipelines for autonomous driving, predictive maintenance and computer vision. - 2017 to 2019, Samsung Electronics: Technical Team Lead and Senior Software Engineer. Natural language generation for a voice assistant. - 2017, University of Stuttgart: Research assistant. Emotion analysis of tweets, combining conditional random fields with convolutional neural networks. - 2015 to 2017, Robert Bosch GmbH: Research software engineer. Research software engineering. - Earlier, Software development: Software developer and founder. Software developer roles, and an e-commerce marketplace he founded in 2013. Areas of expertise: Data engineering and data platforms; Databricks; MLOps and DataOps; Machine learning engineering; Natural language processing; Generative AI and AI agents; AI infrastructure and GPUs; Solution architecture; Cloud and distributed systems. Founder page: https://emolysis.com/about/roozbeh-bandpey. Public profile: https://www.linkedin.com/in/roozbehbandpey/. ## What Emolysis is Emolysis is the agentic lakehouse for data engineering and analytics. Direct a team of agents from your laptop to investigate business questions, develop dashboards, and build and test pipelines for your data platform. Business users want answers to the questions that matter. Data teams need the definitions, transformations and pipelines behind those answers. Emolysis brings these needs into one development workflow, with the person directing the work and reviewing the results. Our approach combines local development and testing with platform-specific pipeline templates. Production pipelines run on the customer's data platform. Databricks is the first design-partner focus; Snowflake and Microsoft Fabric are planned. Emolysis gives people the capabilities of a data engineering and analytics team through a downloadable product. Underneath is a local-first coding agent, built for data engineering leads, platform teams and analytics engineers who run production data on Databricks, Snowflake or Microsoft Fabric. Most production pipelines follow about ten known shapes, and each shape has a correct form on each platform. Emolysis picks the shape that fits your request, fills a template written for your platform, proves the result with golden tests on DuckDB on your machine, and only then deploys it as your platform's native unit. The same engine turns a business question into a gold table and a dashboard you can share. Emolysis does not replace Databricks, Snowflake or Microsoft Fabric as your production platform, or their catalogs, and it is not a hosted service that runs your production jobs. Production runs on your platform, under your account. ## How it works 1. Ask. Start from a business question, such as monthly revenue by region, or name the pipeline you need. Emolysis finds the sources that can answer it: the tables in the platform you connect, sampled to your machine. 2. Confirm the definition. You confirm what the metric means: its measures, grain and joins. The agents send your request, with the schema details they need, to the AI model provider you choose. 3. Build and test. Emolysis fills the template for your platform and runs its golden tests on DuckDB on your machine. A failing test sends it back to the template, not to production. 4. Dashboard, then deploy. You see the dashboard on your machine first. A green run deploys as your platform's native unit, such as a Databricks Asset Bundle, and publishes the dashboard when you ask for one. ## Pipeline shapes Each shape has a template per platform, with named slots, test fixtures and expected outputs (golden tests). Status: templates are written for Databricks, Snowflake and Microsoft Fabric and pass their golden tests on DuckDB; none has passed on a real platform yet, and none is released. - Ingest (batch) (https://emolysis.com/shapes/ingest-batch): Land files, extracts and database tables in bronze tables, typed and checked on load. - Incremental append (https://emolysis.com/shapes/incremental-append): Append only the rows that arrived since the last run, tracked by a watermark. - CDC merge (https://emolysis.com/shapes/cdc-merge): Apply inserts, updates and deletes from a change feed to a target table. - SCD Type 2 (https://emolysis.com/shapes/scd2): Keep the full history of a dimension, with a validity range for every version. - Snapshot (https://emolysis.com/shapes/snapshot): Copy a source in full on a schedule and keep dated copies for a set retention period. - Backfill (https://emolysis.com/shapes/backfill): Re-run a pipeline for a past date range, one partition at a time, without touching the rest. - Late-arriving (https://emolysis.com/shapes/late-arriving): Reprocess the right time windows when facts arrive after the period they belong to. - Dedupe / conform (https://emolysis.com/shapes/dedupe-conform): Turn raw bronze rows into clean silver rows: one row per key, with consistent types and names. - Aggregation / gold (https://emolysis.com/shapes/aggregation-gold): Build the metrics tables that dashboards and reports read, at a declared grain. - Reverse ETL (https://emolysis.com/shapes/reverse-etl): Push curated gold data back into business applications and operational databases, safe to re-run. ## Platforms Connecting a platform loads a platform profile: dialect, table format, merge idiom, incremental tools, deployment unit, compute, sign-in method, known traps and how to sample. Only the templates for your connected platform are offered. - Databricks (https://emolysis.com/platforms/databricks): Deploy target (in development). The first target. Writes for Delta tables and Unity Catalog and deploys as Databricks Asset Bundles. - Snowflake (https://emolysis.com/platforms/snowflake): Deploy target (planned). Writes for streams, tasks and dynamic tables, with Snowflake's own identifier rules. - Microsoft Fabric (https://emolysis.com/platforms/microsoft-fabric): Deploy target (planned). Writes for lakehouses in OneLake and deploys notebooks to your Fabric workspace. - SQL Server (https://emolysis.com/platforms/sql-server): Source (planned). Planned as a source: operational tables and change data from SQL Server, read for your pipelines. - PostgreSQL (https://emolysis.com/platforms/postgresql): Source (in development). Reads tables from PostgreSQL as a source: mirrors its catalog and samples tables into DuckDB on your machine. - DuckDB (https://emolysis.com/platforms/duckdb): Local engine (local dev loop). The local development loop: every pipeline runs and passes its tests on DuckDB before it touches your platform. ## Where you use it Emolysis is one engine with one set of commands, reached the same way from every surface. Status: none of these are released yet. - Desktop app (https://emolysis.com/integrations/desktop-app): The full engine with a workspace view, for macOS, Windows and Linux. In development. - emo CLI (https://emolysis.com/integrations/cli): Every Emolysis command from the terminal, for scripts and CI. In development. - MCP server (https://emolysis.com/integrations/mcp): Emolysis inside any editor or coding agent that supports MCP. In development. - GitHub App (https://emolysis.com/integrations/github): Checks on every pull request: lint, golden tests, cost estimate and a preview link. Planned. ## Data handling How Emolysis handles your data: - Your platform credentials stay on your machine, in its credential store. They are not sent to Emolysis. - Deployed pipelines and queries against your platform run there, under your account; local tests run on your machine. - To write code, the agent sends prompts to the AI model provider you choose. A prompt can include table and column names, schemas and sample values from your data. - A dashboard leaves your machine when you publish it, and only then. Shared dashboards have three visibility settings: anyone with the link, members of your organization (the default), or only you. You can revoke a link or set it to expire. - With your own model key, prompts go to that provider under your key and its terms. With a paid plan's included usage or usage credits (on Enterprise, metered usage), prompts and responses pass through Emolysis's metering service on the way to the model provider. That service is designed not to store or log their content; it records token counts for billing. - When you sign in, Emolysis receives your account identity from the provider you choose: GitHub, Microsoft or Google. Emolysis's services keep your account, organization, plan and usage records. They are designed never to connect to your data platform and never to receive your platform credentials. Data from your tables reaches them only in prompts that pass through the metering service, which is designed not to store or log them, and in dashboards you publish. - The GitHub App is planned. If you install it, it reads the contents of the repositories you choose, to run its checks, and writes check results and comments on their pull requests. - Product telemetry is documented before the first release. The website loads Google Analytics and Microsoft Clarity, and sets their cookies, once a visitor chooses in its cookie banner, whose every choice includes them; the signed-in account and shared dashboards never load them. - Emolysis has not been through a third-party security audit and holds no compliance certifications. Details: https://emolysis.com/security. ## Plans Plans and prices are planned; nothing can be bought yet. Every plan accepts your own model key from the model provider you choose. Requests made with it are billed by your provider and do not count against your plan's limits. - Free: bring your own model key, billed by your provider; the local engine and DuckDB, one platform connection, the core templates and the MCP server. - Pro: included model usage, every platform connection, the full template library, web dashboards and sharing, and the planned GitHub App with pull request checks. - Max: 5x or 20x Pro's included usage, priority at busy times, and early access to new templates and connectors. - Team: per seat, with included model usage for each seat, a shared catalog, an organization workspace, audit export and single sign-on. - Enterprise: no included allowance; model usage at standard metered rates within spend limits that admins set, or an organization key; support terms, and options for running Emolysis in your own environment (planned). Planned prices in US dollars: https://emolysis.com/pricing. ## Documentation - Introduction (https://emolysis.com/docs/introduction): What Emolysis does, how it works on your data platform, where each part stands today, and how these docs are organized, page by page. - How Emolysis works (https://emolysis.com/docs/how-it-works): The fixed path from a request to a deployed pipeline: connect, describe, pick a shape, fill a template, test on DuckDB, deploy, publish. - Installation (planned) (https://emolysis.com/docs/installation): What Emolysis installs as, on which systems, and what exists today. No build is released; the emolysis package name is only a placeholder. - Quickstart (planned flow) (https://emolysis.com/docs/quickstart): A first Emolysis session, step by step: a local file, a tested gold table, a dashboard, then a tested pipeline deployed on Databricks. - Projects and emolysis.yml (https://emolysis.com/docs/projects): The Emolysis project folder: models, pipelines, tests, the emolysis.yml project file and the local lakehouse for samples. - Pipeline shapes (https://emolysis.com/docs/shapes): The ten pipeline shapes, how the agent chooses one, how shapes combine into real pipelines, and what happens when no shape fits your request. - Templates and slots (https://emolysis.com/docs/templates): What an Emolysis template contains, the eleven slot types, how slots are filled and validated, and how to write your own templates. - Golden tests on DuckDB (https://emolysis.com/docs/golden-tests): How fixtures and expected outputs prove a pipeline on your machine before deploy, when the tests run, and what they do not prove. - Platform profiles (https://emolysis.com/docs/platform-profiles): What a platform profile records, from dialect and table format to known traps, and how the agent uses it on every request in your project. - Connecting Databricks (https://emolysis.com/docs/connect-databricks): How you connect a Databricks workspace to Emolysis: sign-in, OAuth, workspace and compute, the catalog mirror, sampling and what a deploy makes. - Connecting Snowflake (https://emolysis.com/docs/connect-snowflake): Snowflake is planned after Databricks, tested only on simulated services. What the connection needs, what its profile covers and what is not decided. - Connecting Microsoft Fabric (https://emolysis.com/docs/connect-fabric): Microsoft Fabric is planned after Databricks, tested only on simulated services. What the connection needs and what its profile covers. - Sources (https://emolysis.com/docs/sources): SQL Server and PostgreSQL as sources: Emolysis reads from them and never deploys to them. What that means, the shapes they feed and what is not decided. - Deploying (https://emolysis.com/docs/deploying): How a green pipeline becomes your platform's native unit: Databricks Asset Bundles, Snowflake SQL or Fabric items, with pull request gates. - Dashboards from a question (https://emolysis.com/docs/dashboards): From a business question to a semantic model, a tested gold table and charts. The seven chart types and how publishing works. - Sharing dashboards (https://emolysis.com/docs/sharing): Publishing a dashboard as a link: a stable link with revisions, three visibility settings fixed per link, snapshot links that can expire, and revoking. - Chart types (https://emolysis.com/docs/chart-types): The seven chart types Emolysis dashboards use, what each takes, how numbers are combined and formatted, and how many series a chart shows. - The emo CLI (https://emolysis.com/docs/cli): The emo commands: init, connect, login, check, token, dashboard refresh, mcp, doctor and run, with exit codes, skills and how emo fits into CI. - The MCP server (https://emolysis.com/docs/mcp-server): Using emo mcp from an editor or coding agent that supports MCP: configuration, tool names, signing in with your Emolysis account and errors. - Editors and coding agents (https://emolysis.com/docs/editors): How editors and coding agents that support MCP use Emolysis: setup buttons, ready-made configs and skills, and what your tool sends to its model. - GitHub checks (https://emolysis.com/docs/github-checks): Lint, golden tests and a cost estimate on every pull request, with emo check in your own CI; the GitHub App, which adds a preview, is planned. - Model keys and credits (https://emolysis.com/docs/model-keys-and-credits): Bring your own key from the model provider you choose, on any plan, or use a paid plan's model usage. What each means for cost and for your data. - Data handling (https://emolysis.com/docs/data-handling): Exactly what leaves your machine when you use Emolysis, and when: prompts, published dashboards, sign-in and the GitHub App. - Troubleshooting (https://emolysis.com/docs/troubleshooting): The nine Emolysis error codes and what to do about each, plus common problems with sign-in, tests, deploys, links and MCP. - Error codes (https://emolysis.com/docs/error-codes): The nine error codes every Emolysis surface returns, what each one means, the usual causes, and what to do about it when one appears. ## Frequently asked questions - Does my data leave my machine? (https://emolysis.com/faq/does-my-data-leave-my-machine): Some of it can: prompts go to the model provider you choose and can include schemas and sample values, and a dashboard leaves only when you publish it. - How do dashboards from a question work? (https://emolysis.com/faq/how-dashboards-from-a-question-work): You type a business question, and Emolysis builds a tested gold table behind it and picks charts for you to review before you publish a link. - How does Emolysis work with GitHub? (https://emolysis.com/faq/how-emolysis-works-with-github): Your pipelines live in your own repository, and checks on each pull request, from emo check in your CI or the planned GitHub App, are the gate for every deploy. - Is Emolysis free? (https://emolysis.com/faq/will-emolysis-be-free): There is a Free plan at $0, and because it is bring your own key, you pay your model provider directly and Emolysis charges nothing for it. - Is there a release date for Emolysis? (https://emolysis.com/faq/when-will-emolysis-be-available): There is no release date yet, because Emolysis is in private development, and the news page announces availability when there is one. - What are pipeline shapes? (https://emolysis.com/faq/what-are-pipeline-shapes): A pipeline shape is a recurring kind of data pipeline with a known correct form, and about ten shapes cover most production work. - What is Emolysis? (https://emolysis.com/faq/what-is-emolysis): Emolysis is the agentic lakehouse for data engineering and analytics, made by Bandpey GmbH in Munich, that puts a team of agents at your direction. - Which platforms does Emolysis support? (https://emolysis.com/faq/which-platforms-will-emolysis-support): Databricks is first, Snowflake and Microsoft Fabric are planned, PostgreSQL is in development as a source, SQL Server is planned as one. - Who makes Emolysis? (https://emolysis.com/faq/who-makes-emolysis): Emolysis is made by Bandpey GmbH, a company in Munich, Germany, led by CEO Roozbeh Bandpey, and it is in private development. - Can I join early access? (https://emolysis.com/faq/can-i-join-early-access): Early access is by invitation, starting with data engineering teams on Databricks, and you ask for it with the request form or by email to the team. - Is Emolysis open source? (https://emolysis.com/faq/is-emolysis-open-source): The core is closed source, while the template format and the setup configs for editors and coding agents are public under the MIT license. - What does bring your own key mean? (https://emolysis.com/faq/what-is-bring-your-own-key): You add a key from the model provider you choose, the agent uses it, that provider bills you directly, and Emolysis adds nothing to that bill. - What does the AI model provider see? (https://emolysis.com/faq/what-does-the-model-provider-see): It sees the agent's prompts and the responses it returns, which can include table and column names, schemas, templates and sample values from your data. - What does the GitHub App check? (https://emolysis.com/faq/what-will-the-github-app-check): The GitHub App is planned; it checks four things on every pull request: lint, golden tests on DuckDB, a cost estimate and a preview dashboard link. - Which ten shapes does Emolysis cover? (https://emolysis.com/faq/which-ten-shapes): Ingest (batch), Incremental append, CDC merge, SCD Type 2, Snapshot, Backfill, Late-arriving, Dedupe / conform, Aggregation / gold and Reverse ETL. - Who can see a dashboard I share? (https://emolysis.com/faq/who-can-see-a-shared-dashboard): You choose when you publish from three settings, anyone with the link, members of your organization or only you, with organization as the default. - Who is Emolysis for? (https://emolysis.com/faq/who-is-emolysis-for): Emolysis is for people who own production data pipelines on Databricks, Snowflake or Microsoft Fabric, and for analysts who want a dashboard from a question. - Why is Databricks first? (https://emolysis.com/faq/why-databricks-first): Databricks has the complete set of APIs Emolysis needs to prove the whole loop, from a question to a tested, deployed pipeline and a shared dashboard. - Can I change who can open a shared dashboard? (https://emolysis.com/faq/change-who-can-open-a-shared-dashboard): Not on its current link: revoke the link, then publish the dashboard again with the setting you want, which makes a new link with a new URL. - Can I run the checks in my own CI? (https://emolysis.com/faq/run-checks-in-my-own-ci): Yes, a reusable GitHub Actions workflow, in preview, runs emo check in your own CI; it needs the emo command line, which is not released yet. - Can I use my own key on a paid plan? (https://emolysis.com/faq/can-i-use-my-own-key-on-a-paid-plan): Yes, every plan accepts your own model key, and requests made with it are billed by your provider and do not count against your plan's limits. - How can I contact the team? (https://emolysis.com/faq/how-can-i-contact-the-team): Email hello@emolysis.com, which is the one channel for general questions, early access, press and security reports while Emolysis is in private development. - How is Emolysis different from a general coding agent? (https://emolysis.com/faq/different-from-a-general-coding-agent): A general agent writes whatever a prompt suggests; Emolysis starts from a platform profile, tested templates and golden tests on your machine. - Is there a date for Snowflake and Microsoft Fabric? (https://emolysis.com/faq/when-snowflake-and-fabric): There are no dates yet: both are planned after Databricks, and the news page announces each one when its templates pass their tests there. - What if my pipeline does not fit one of the ten shapes? (https://emolysis.com/faq/pipeline-does-not-fit-a-shape): Most real pipelines are several shapes in a row, and when a request fits none the agent says so instead of improvising code it cannot test. - Where are my platform credentials stored? (https://emolysis.com/faq/where-are-platform-credentials-stored): They are kept in your operating system's credential store and not sent to Emolysis, whose services never connect to your data platform. - Which operating systems does the desktop app support? (https://emolysis.com/faq/which-operating-systems): The desktop app is for macOS, Windows and Linux, with no build released yet, and the emo command line and MCP server cover the same three systems. - Can I update a shared dashboard? (https://emolysis.com/faq/can-i-update-a-shared-dashboard): Yes, a dashboard keeps one stable link and each publish adds a revision under it, so the link you sent stays the same and shows the latest numbers. - Does Emolysis store my data on its servers? (https://emolysis.com/faq/does-emolysis-store-my-data): Only what you publish, because Emolysis's services hold your account, plan and usage records, and the dashboards you choose to publish. - Does Emolysis work offline? (https://emolysis.com/faq/will-emolysis-work-offline): Partly: golden tests on DuckDB with local files work offline, while writing code, deploying and sharing a dashboard all need a network connection. - Does this website use cookies or analytics? (https://emolysis.com/faq/does-this-website-use-cookies): Yes, once you choose in the cookie banner; before that it sets no cookies and keeps nothing in your browser but your theme. - What do the paid plans add? (https://emolysis.com/faq/what-do-paid-plans-add): Pro adds every platform connection, sharing and GitHub checks, Max more included usage, Team shared workspaces, and Enterprise controls and support. - What does an Emolysis project look like? (https://emolysis.com/faq/what-does-a-project-look-like): A plain folder you own and keep in your own repository, with models, pipelines, tests and an emolysis.yml file that names the platform. - What does local-first mean for Emolysis? (https://emolysis.com/faq/what-does-local-first-mean): Development runs on your machine with DuckDB and production runs on your platform, but that does not mean that nothing leaves your machine. - What is a golden test? (https://emolysis.com/faq/what-is-a-golden-test): A golden test runs a pipeline on a fixed input and compares its output with an expected output row for row; a failure sends the agent back to the template. - What is a platform profile? (https://emolysis.com/faq/what-is-a-platform-profile): A platform profile describes a data platform for the agent, which loads it when you connect a workspace and writes code the way that platform expects. - Can I limit what the agent sends in prompts? (https://emolysis.com/faq/limit-what-prompts-include): No dedicated setting yet: you limit what the agent sees with a development workspace, non-sensitive tables and synthetic test fixtures. - Can I move a pipeline from one platform to another? (https://emolysis.com/faq/move-a-pipeline-between-platforms): Yes, as an explicit step in which the pipeline is translated to the target platform's dialect and its golden tests run again. - Can I revoke or expire a shared link? (https://emolysis.com/faq/revoke-or-expire-a-shared-link): You can revoke any shared link at any time, which deletes the data you published with it, and only a snapshot link can also have an expiry date. - Does Emolysis replace my data platform or catalog? (https://emolysis.com/faq/does-emolysis-replace-my-platform): No, Emolysis sits on top of the platform you already run and deploys your platform's native unit, which your team can review and operate. - How do I hear about releases? (https://emolysis.com/faq/how-will-i-hear-about-releases): On the news page and its RSS feed, which is where we announce each release, each new platform and any change to the plans and their prices. - How is Max different from Pro? (https://emolysis.com/faq/how-is-max-different-from-pro): Max is for people who build with the agent all day, and it adds 5x or 20x Pro's included usage, priority access at busy times and early access. - Why test on DuckDB instead of on my platform? (https://emolysis.com/faq/why-test-on-duckdb): DuckDB runs on your machine with no cluster, so a golden test takes seconds and spends no warehouse compute, which makes testing on every save practical. - Can Emolysis read from SQL Server or PostgreSQL? (https://emolysis.com/faq/sql-server-and-postgresql-sources): PostgreSQL is in development as a source and SQL Server is planned: Emolysis reads from them, lands the data on your platform and never deploys to them. - Can I write my own templates? (https://emolysis.com/faq/can-i-write-my-own-templates): Yes, the template format is public under the MIT license, and you can write templates for your own recurring patterns and use them in your projects. - How do Team seats work? (https://emolysis.com/faq/how-will-team-seats-work): Team is for 2 to 150 people, with standard seats at $25 and premium seats at $125 per seat a month, and lower prices when billed annually. - What happens if my dashboard's link was revoked? (https://emolysis.com/faq/what-happens-when-a-link-was-revoked): The dashboard on your machine is untouched, and your next publish from the app makes a new link and says the old one was replaced; a refresh never makes one. - What permissions does Emolysis need on my platform? (https://emolysis.com/faq/platform-permissions): Emolysis acts with the permissions of the account you sign in with, no more, so a role limited to a development workspace limits what it can do. - Which AI model does Emolysis use? (https://emolysis.com/faq/which-ai-model-does-emolysis-use): Emolysis works with your own key from the model provider you choose, on any plan, or with a paid plan's included model usage instead of a key. - Can I use Emolysis from my editor or coding agent? (https://emolysis.com/faq/use-emolysis-from-my-editor): Yes, the MCP server, emo mcp, lets any editor or coding agent that supports MCP use the same commands as the desktop app, with one config entry. - How does Enterprise pricing work? (https://emolysis.com/faq/how-will-enterprise-pricing-work): Enterprise is US$20 per seat a month billed annually, plus model usage at metered rates, with a 20-seat minimum for self-serve, at planned prices. - Is Emolysis certified for SOC 2 or similar standards? (https://emolysis.com/faq/security-certifications): No, Emolysis is in private development and has not been through a third-party audit, penetration test or compliance certification. - What chart types do dashboards support? (https://emolysis.com/faq/what-chart-types): The chart spec defines seven types, bar, line, area, scatter, pie, KPI and table, and every chart also lists its data in a table. - Can I pay annually, and does it cost less? (https://emolysis.com/faq/can-i-pay-annually): Yes for Pro and Team, where annual billing costs less per month, while Max is billed monthly only and Enterprise annually only, at planned prices. - Does Emolysis deploy anything without my approval? (https://emolysis.com/faq/deploy-without-approval): No, deploying is a step you take yourself, and only after lint, a DuckDB dry run and the golden tests on your machine have all come back green. - How do usage credits work? (https://emolysis.com/faq/what-are-emolysis-credits): Usage credits on Pro, Max and Team keep the agent working at standard metered rates after you reach your plan's included model usage. - How do usage limits work, and what if I reach one? (https://emolysis.com/faq/how-will-usage-limits-work): Included usage is measured by the work the agent does, and at a limit you can wait, use your own key, change plan or turn on usage credits. - Does Emolysis charge for my warehouse compute? (https://emolysis.com/faq/will-emolysis-charge-for-warehouse-compute): No, deploys and production runs use your platform's compute and appear on your platform's bill, and local iteration uses no cluster hours. - Can I buy a plan today? (https://emolysis.com/faq/can-i-buy-a-plan-today): No, Emolysis is in private development, nothing is for sale, and the prices on this site are planned prices that may change before release. ## Company and contact Emolysis is made by Bandpey GmbH, Munich, Germany (https://bandpey.com). - Email: hello@emolysis.com (early access, security reports, press and general questions). - GitHub: https://github.com/emolysis (public repositories). - Imprint: https://emolysis.com/legal/imprint. - News and release announcements: https://emolysis.com/news.