arcodash VS DeckCipher

arcodash's answer

AI runs through the whole loop, from question to alert. Ask in plain English and an AI agent writes the SQL, runs a read-only preview, checks the result and retries until it holds up. Then it watches the data: it suggests which data quality checks to add, learns what normal looks like so you don't set thresholds by hand, and when an alert fires it tells you why. It slices the data and names the segment that moved, right in the Slack, email or PagerDuty message. Dashboards and data checks live in one tool, on the same SQL.

arcodash's answer

Data analysts, analytics engineers and small data teams who own the dashboards the business relies on, plus the less-technical people who need numbers from the warehouse and would rather ask in plain English. Typically startups and mid-size companies on Postgres, Snowflake, BigQuery, ClickHouse or similar.

arcodash's answer

The connect, query, visualize, dashboard, alert workflow is one a lot of data teams know from older self-hosted query tools. I wanted to rebuild it for the AI era: you ask a question and get a query that actually ran, and the tool keeps an eye on the data itself, so it answers "can I trust this number?" and not only "what is the number?". When something breaks it should tell you why, not just that a check failed. The name comes from the arc: it connects the dots, and it bears load. I build arcodash as a solo founder.

arcodash's answer

Rust (Axum, Tokio, SeaORM), PostgreSQL, Redis, React with TypeScript (Vite, TanStack Query, Recharts, Tailwind), Astro for the website, hosted on Google Cloud behind Cloudflare. AI runs on Gemini, OpenAI or Anthropic models, with an agent loop streamed to the browser.

arcodash's answer

Most teams run one tool for dashboards, a second for data quality, and a chat assistant on the side that doesn't know their schema. arcodash is one tool: the AI builds a profile of each data source (sample values, relationships, table and column descriptions), so its SQL fits your actual data, and the same engine that draws the chart alerts you when the number is wrong. It's SQL-first, so every AI answer is a query you can read and edit. Bring your own Gemini, OpenAI or Anthropic key, and pricing is flat, not per seat: $59/month on Team or $300/month on Org, unlimited seats on both. 14 days free, no card.