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Adapt is the universal AI agent that runs on your company brain. Gets instant answers for complex questions, automate workflows on-demand, schedule tasks, and build internal apps with full context of your business. Set it up once and everyone can use it on Slack, web, or mobile.
GitHub AdaptAdapt's answer:
Adapt publicly lists or features the following customers and customer examples:
Adapt's answer:
Adapt is different because it is built as a shared AI agent for company work, not a private chatbot or single-purpose automation bot.
Teams can ask natural-language questions across connected business systems, get cited answers grounded in live company data, and then take action from the same workflow. Adapt works in Slack and the web app, can automate recurring workflows and scheduled tasks, and can build internal apps and dashboards from live company data.
The strongest difference is the shared-work model: a Slack thread can become an investigation, a report, a workflow, or an internal tool that the team can see, refine, and keep using together.
Adapt's answer:
Choose Adapt when the work you want AI to handle crosses multiple tools, teams, and data sources.
Many AI assistants are either personal chatbots, search tools, or single-app automations. Adapt is designed for shared business workflows: it can gather context from connected systems, reason over the information, provide evidence-backed answers, and take action such as posting to Slack, creating reports, updating records, or triggering workflows.
Adapt is especially useful for teams that already work in Slack and need AI to operate with company context. It also includes business-grade controls such as organization-level access controls, audit logging, encryption in transit and at rest, and SOC 2 Type I certification.
Adapt's answer:
Adapt is built for business teams at startups and scaling companies whose work spans multiple systems: data warehouses, CRMs, support tools, billing platforms, project management systems, Slack, and internal docs.
The primary audience includes leadership, operations, sales, marketing, product, engineering, customer support, and data teams. It is a strong fit for teams that need fast answers from company data, recurring reports, cross-system workflows, and internal tools without waiting on data, engineering, or operations teams for every request.
Adapt is especially useful for teams that already collaborate in Slack and want AI to work where decisions and follow-up already happen.
Adapt's answer:
Adapt was built around a simple belief: the most valuable work in a company is shared, but most AI tools are still personal and disconnected from the systems where work actually happens.
The product grew from the need for one AI agent that can understand company context, investigate across business tools, and help teams act together. Adapt's public product framework is Ask, Understand, Act: ask in natural language, let Adapt gather context from connected tools, then use the answer to create reports, update systems, automate workflows, or build internal apps.
Adapt also uses its own product internally. In its blog post "How Adapt uses Adapt," the team describes using Adapt across engineering, marketing, sales, leadership, and product workflows, from debugging production issues to competitive intelligence, daily company briefings, and CRM updates.
Adapt's answer:
Adapt's public documentation focuses on product architecture and capabilities rather than publishing a full internal engineering stack.
The core technologies and product components described publicly include:
In practical terms, Adapt is built to connect large language models with live company systems, permissions, workflow automation, and collaborative surfaces like Slack.
Based on our record, GitHub seems to be more popular. It has been mentiond 2470 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
This is why eval and observability ship as a unit, not as separate purchases. agent-eval scores and gates the output โ the tiers above, drift, hallucination. AgentLens captures the trace of how the agent got there: every model step and tool call, the resolved inputs, the raw outputs, the trajectory. Two things fall out of that:. - Source: dev.to / 9 days ago
The real fragility is in trying to constrain arguments. The docs are explicit that a pattern like Bash(curl http://github.com/ *) fails to do what it looks like it does. It won't match curl -X GET http://github.com/... (option before the URL), curl https://github.com/... (different protocol), curl -L http://bit.ly/xyz (redirects to GitHub), URL=http://github.com && curl $URL (variable), or curl http://github.com... - Source: dev.to / 10 days ago
Fallback chains โ og:title โ twitter:title โ- SSRF protection โ if you fetch user-supplied URLs, you MUST block
localhost, RFC-1918 ranges, and internal hostnames, or your preview endpoint is a proxy into your own infrastructure- Caching โ you do not want to re-fetch a URL on every render
- Rate limiting โ a public...
- Source: dev.to / 12 days ago
$ git pull Remote: Repository not found. Fatal: repository 'https://github.com//.git/' not found. - Source: dev.to / 14 days ago
// ==UserScript== // @name GitHub -> Obsidian Task // @namespace obsidian // @version 1.0 // @match https://github.com/*/*/issues/* // @match https://github.com/*/*/pull/* // @grant GM_setClipboard // ==/UserScript== (function () { 'use strict'; function getTitle() { return document.querySelector("bdi")?.textContent.trim(); } function copyTask() { ... - Source: dev.to / 16 days ago
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