Alternatives
Products that do what ReportIQ does
Stop writing client reports. Let AI handle them.
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
Query data to build dashboards and generate detailed reports
Apr 2026 · orcasheets.ai
- 11NA
2023 · narrative.bi
- 12
- 13
- 14AD
2023 · gist.github.com
- 15BA
Bin is an AI business intelligence analyst that turns data into dashboards. Our goal is to make creating dashboards simpler to do than no-code alternatives like PowerBI and Tableau while preserving the powerful customization abilities of raw SQL and Python. Here’s a quick demo: https://www.youtube.com/watch?v=Fsh8M3hIjDA. Customers from our previous product wanted custom dashboards but didn’t want to spend on technical staff to build them. They wanted customizability of the dashboard yet simplicity of the building experience. So, we studied the approaches of Devin, Claude…
2025 · bi.new
- 16NB
Michael and Yury here – we're building a no-code analytics platform for growth teams that automatically generates actionable data insights. After working in the data space for many years, we realized there was still a huge gap in the marketing analytics market. Growth teams have so much marketing and advertising data, yet this siloed data is not actionable. The existing BI and search-driven analytics solutions are designed for data-savvy people. In our experience (previously built an NLP company called FriendlyData), non-technical people just don't know what questions to ask. So we decided…
2022 · narrative.bi
- 17
- 18
- 19
BidIQ▲7Save connects, screen client risk & write Upwork proposals
Jul 2026 · chromewebstore.google.com
- 20
Practice real interviews with AI and get instant feedback.
May 2026 · interviewiq-app.vercel.app
- 21
- 22
- 23
- 24FA
Hey HN, we built an Econ+Finance database to let AI agents do investment research. We spend a lot of tokens to organize macro releases and SEC filings into a clean format, so that your agents have more context to do actual analysis. The problem AI agents are great at data analysis. But they become ineffective if most of their context window is spent on gathering and cleaning data, instead of validating hypotheses. Data in the wild is messy and rarely standardized. Definitions and measurements change over time. This problem is compounded by a fragmented data universe. Point solutions exist…
Jul 2026 · github.com
Ranked by how close each launch is in meaning, then by votes. Refine with a description →