Akkio

Last updated: 2026-07-22

Akkio builds forecasting models roughly 100x quicker than typical AutoML pipelines, letting non-technical teams ask plain-English questions instead of writing SQL or building dashboards by hand. It targets marketing agencies, sales operations teams, and growth marketers who need forecasts from structured CRM or spreadsheet data without a dedicated data science team.

About Akkio

Akkio was founded in June 2019 in Cambridge, Massachusetts, and has raised $18 million in total funding, including a $15 million Series A led by Bain Capital Ventures and MIT Startup Exchange. Its core interface, Chat Explore, lets users ask plain-English questions about a dataset, such as 'show me sales trends by region last quarter,' and get an automatic chart or summary in response. Underneath sits a no-code pipeline builder covering time series forecasting, lead-scoring and churn classification, and generative reports that write up trends and anomalies without a human building the chart first. It also connects to common CRMs and data warehouses out of the box, and exposes a REST API (currently in v2 beta) via an X-API-Key header for programmatic access.

Pricing

Free plan (view-only, no editing). Basic at $49/user/month (Chat Explore, BI dashboards). Pro at $99/user/month (time series forecasting, production model training). Build-On Package from $999/month for agencies (white-label + full API access). Enterprise pricing is custom.

Key Features

• Chat Explore: A natural language query layer that accepts plain-English questions about uploaded datasets and returns visualizations and summaries automatically, eliminating the need to write SQL or build charts manually.
• Rapid Model Training: Akkio's proprietary AutoML pipeline trains classification and regression models in as few as 10 seconds, so analysts can iterate on a forecast live in a meeting instead of waiting on a data science queue.
• Time Series Forecasting: Automatically selects appropriate forecasting algorithms based on historical data patterns to predict sales pipeline, website traffic, campaign performance, or any numerical metric tracked over time.
• Generative BI Dashboards: Produces automated insight reports and live dashboards from uploaded data, including written summaries of trends and anomalies, without requiring a BI tool or data analyst to configure visualizations.
• White-Label Analytics (Build-On): The Build-On Package lets agencies deliver AI-powered analytics to clients under their own brand, with a white-labeled Chat Explore interface and API access to embed predictions in client-facing products.
• Native CRM and Data Warehouse Connectors: Out-of-the-box integrations with HubSpot, Salesforce, Snowflake, Google BigQuery, and Google Sheets allow users to pull live data without building ETL pipelines or uploading CSV files manually.

Pros

• Fast enough model training means business analysts can iterate on a forecast in a single meeting instead of waiting days on a dedicated data science team to build and validate a model.
• Reselling under the Build-On tier turns Akkio into a revenue line for marketing agencies: no custom development is needed to put a white-labeled Chat Explore in front of clients.
• Integrates directly with Salesforce, HubSpot, and Snowflake without building ETL pipelines, meaning sales and marketing teams can start predicting from live CRM data in under 30 minutes.

Cons

• The platform is limited to structured tabular data (spreadsheets and databases) and cannot handle images, video, audio, or raw text NLP tasks, excluding a large class of AI use cases.
• The free plan is view-only, with no editing or model training, so any meaningful evaluation requires upgrading to a paid plan first.
• Advanced data scientists who need custom model architectures, feature engineering control, or deployment to custom infrastructure will find Akkio's automated approach too opaque compared to Python-based tools like scikit-learn or AWS SageMaker.

Visit Akkio Official Website