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Genloop is an agentic data intelligence platform that gives every person and AI agent in a company verified, accurate answers from their own data, without copying it anywhere.
Most BI tools stop at a dashboard. When a question isn't already answered there, someone has to find an analyst and wait. Genloop closes that gap: teams ask questions in plain English and get answers backed by visible logic, the same way every time.
At the centre is the Living Context Graph, a working model of an organisation's metrics, relationships, and business rules. It lets Genloop reason correctly across multiple databases and apps, not just a single table.
On Spider 2.0-Snow, the hardest public benchmark for enterprise text-to-SQL reasoning, Genloop ranks first at 96.70%, ahead of major cloud and enterprise vendors.
Genloop reads data directly from its source, with no ETL and no copies, so setup takes minutes. It is SOC2 Type II and ISO 27001 certified, with a free tier and no credit card required.
Genloop is built for data teams tired of being the bottleneck, and for the humans and AI agents around them who just want a straight, correct answer.
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Genloop's answer:
Genloop's Living Context Graph continuously builds a working model of an organisation's metrics, relationships, and business rules, so answers stay accurate across multiple data sources instead of just one connected warehouse.
It reasons and joins data live, in place, with no ETL and no copies, and every answer is deterministic and traceable: ask the same question twice and get the same verified result.
On Spider 2.0-Snow, the hardest public benchmark for enterprise text-to-SQL reasoning, Genloop ranks first at 96.70%, ahead of major cloud and enterprise vendors.
Genloop's answer:
Most alternatives are either a single-warehouse copilot (Snowflake Cortex, Databricks Genie) or a BI tool with AI bolted on top (Power BI Copilot, Tableau Pulse).
Genloop is ecosystem-neutral: it reasons across multiple warehouses and business apps at once instead of one, and treats accuracy as the deciding metric rather than an add-on, since a wrong number costs more than the dashboard it replaced.
Teams get that accuracy without a migration project, because Genloop reads data directly from the source.
Genloop's answer:
Enterprise data leaders and practitioners: heads of data and analytics, analytics engineers, and data product managers, along with the finance, sales, product, and operations teams they support, in organisations where a wrong number carries real cost.
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You're building an app that generates images, transcribes audio, or synthesizes speech. Two API platforms keep showing up in your research: Replicate and deAPI. They run many of the same open-source models and charge per use. - Source: dev.to / about 1 month ago
Replicate: Provides APIs for integrating diverse hosted models into shared pipelines. - Source: dev.to / about 2 months ago
Running AI models in production typically requires managing complex infrastructure, GPUs, and scaling challenges. Replicate simplifies this by providing a cloud API to run thousands of AI models without managing any infrastructure. - Source: dev.to / 7 months ago
Before diving into how vision prompting works, letโs first look at where we can put it to the test. In this case, weโll be using several endpoints available on Replicate, which weโve optimized with Pruna to make them cheaper, faster, and more efficient. All of Prunaโs models are available here. - Source: dev.to / 8 months ago
Take Perplexity they didnโt just call the OpenAI API; they built a full-stack retrieval engine with caching, ranking, and live search inference. Or Replicate, which gives developers an API to run open-source models at scale, no data center required. RunPod makes GPU clusters accessible for indie builders, and Mistral is shipping models that make even GPT-4 blink twice. - Source: dev.to / 8 months ago
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