opensourcecopilotalternative.comUpdated 2026-10-18
Google AI Studio is not Copilot Studio's rival: the open-source comparison
Copilot Studio bills agents in Copilot Credits inside a Microsoft tenant. Google AI Studio is a prompt-to-app playground. Google's answer to Copilot Studio is Gemini Enterprise, and all three rent you the runtime. Kortix is the open-source AI Operating System, and its agents live in a git repo you own.
The four products, on the questions that decide a purchase
Kortix first, then each rival described from its own current documentation.
The manifest header that puts an agent in a file
# yaml-language-server: $schema=https://kortix.com/schema/kortix.v2.schema.json# Kortix project manifest. Source of truth for project-wide config that# lives in git alongside the code. `kortix_version` pins the schema so# the platform can evolve safely. v2 manifests are YAML-only, with one# `agents:` map per project — GOVERNANCE ONLY (connectors/secrets/# kortix_permissions/skills/workspace/enabled), plus `file`, the path of the# agent's `.md`. Agent BEHAVIOR (description, model, mode, temperature,# permission, the prompt itself, …) lives entirely in that `.md`'s# frontmatter + body — a stock OpenCode agent file works as-is.# Project layout — harness-neutral content at the root:# agents/<name>.md one file per agent (`agents.<name>.file`)# skills/<name>/SKILL.md skills, loaded by every harnessThe starter template's own header, quoted from the public repository. Behavior lives in the agent's markdown file; kortix.yaml carries governance only.
What each of the three products actually is
Microsoft Copilot Studio builds agents that publish into Microsoft's own surfaces: Teams, Microsoft Copilot, SharePoint, or a website. An agent is created inside a Power Platform environment, and that is where it stays.
Google AI Studio does a different job. Google's own documentation describes Build mode as prompt-to-app. Describe the thing you want, and AI Studio generates a web app with a React front end and a Node runtime, or a Kotlin Android app. Your Gemini API key is configured for you as a server-side secret, and the result deploys to Cloud Run or syncs to a GitHub repository.
Google's answer to Copilot Studio is Gemini Enterprise. On Google Cloud's business page, Gemini Enterprise is the agent working inside email, documents, code and business apps, running under each person's existing permissions. The machinery for building your own sits in the Gemini Enterprise platform: Agent Studio, the Agent Development Kit, Model Garden. The URL Google has long used for its agent builder, cloud.google.com/products/agent-builder, now serves that platform's page. Three products do three jobs here: a model workbench with an API key, a tenant-bound agent studio, and a business agent with a build layer underneath.
What you build, and where the thing you built lives
In AI Studio you build a prompt, an application, and an API key. The project stays in AI Studio until you export the code as a ZIP or sync it to GitHub. From then on it is ordinary source code in an ordinary repository.
In Copilot Studio you build an agent, its topics and its tools, then publish it into a Microsoft channel. The definition lives in a Power Platform environment on Microsoft's cloud, versioned through Microsoft's release pipelines and governed from the Power Platform admin center.
In Gemini Enterprise you build agents grounded in enterprise data, either visually in Agent Studio or as code against the Agent Development Kit. Either way they are deployed into a Google Cloud project. The code you write with the kit is yours. The machine it executes on is Google's.
Kortix keeps the definition in the repository from the first minute. An agent is a markdown file under agents/ plus a governance block in kortix.yaml, and the starter manifest's own header says exactly that. Skills, memory and connector grants sit beside it in the same repo, and each session boots its own cloud computer on its own branch. Session work reaches main through a change request a person approves, with merge default-deny for agents.
Three meters, and only one of them is on your side of the fence
Microsoft's meter is credits. "Copilot Credits are the common currency across Copilot Studio capabilities. You can get them through pay-as-you-go meters, prepurchase plans, and Copilot Credit prepaid pack subscriptions," Microsoft's billing and licensing page states, adding that "starting on September 1, 2025, the common currency for agents changed from messages to Copilot Credits." The same page is explicit about carryover: unused Copilot Credits do not roll into the next month. The Copilot Studio account a maker uses costs nothing, but a tenant prepaid Copilot Credit pack subscription has to exist before anyone can get that account. A trial account cannot publish an agent.
Google runs two meters. The Gemini API has a free tier and paid tiers priced per token (Gemini API pricing). Google's AI Studio documentation warns that a shared app's API calls count toward your usage limits (Build mode). Deploying to Cloud Run bills separately. Enterprise on that same pricing page is a contact-sales line. Google Cloud's platform page meters it as Agent Compute, Agent Memory and Agent Storage alongside token pass-through (Gemini platform pricing). Google publishes no public price for Gemini Enterprise, so you price it through Google Cloud sales; the Gemini Enterprise Plus edition can be tried at no cost for 30 days without sales assistance (Google Cloud).
Kortix's meter depends on where you run it. Self-host is free. Managed Cloud is a subscription, and leaving costs you nothing you built.
What survives the vendor change
Every product here answers one purchasing question in the first meeting and a different one in year two: when we change vendors, what walks out with us? From Copilot Studio, what leaves is architecture. The agent is a set of records in a Power Platform environment, wired to Microsoft connectors and identity. Moving it to another runtime means rebuilding it there. Microsoft ships deploy-from-Git with an auditable history, which helps review, though the running agent is still the one in the environment.
AI Studio gets the export part right in a way that deserves credit. The generated code leaves as a ZIP or a repository, and the API key becomes an environment variable wherever you host it. The application keeps working outside Google. What does not leave is the studio itself, so prompt iteration and the app's identity stay inside Google's product.
Gemini Enterprise splits the same way. Agent Development Kit code is yours and can be redeployed, but the agents as deployed objects, their permissions and their audit trail belong to the Google Cloud project you are renting.
Kortix treats that as the design constraint rather than an afterthought. The agent, its skills, its permissions and its connectors are files in one git repo you own, so the definition of the work is versioned, diffable and portable, and a change to it arrives as a diff. Per-resource permissions for people and agents. Roles, groups, and an audit trail. The runtime is yours as well: run it on Kortix Cloud, in your VPC, or on your own on-prem network. Self-host is free.
When each rival is the right call
Reach for AI Studio when the job is to find out whether a model call works. It is a fast place to hold a prompt, look at the output, and leave with a key. For a prototype that becomes your application, there is nothing to migrate, because the code was always yours.
Reach for Copilot Studio when the agents have to live where the Microsoft data lives: SharePoint, Teams, Dataverse, under the data policies and audit trail your Microsoft team already runs from the Power Platform admin center, on a published rate card. For a Microsoft-first company the plumbing is already paid for and the governance already staffed.
Reach for Gemini Enterprise when Google Cloud is already the data platform, the agents need BigQuery-grade grounding under one set of permissions and one bill, and a Google sales relationship is the one you already have.
Choose Kortix when the agent definition has to be yours and the model has to be replaceable. Those three fits are real, and in each one the definition sits comfortably inside a single vendor's product. The moment a second model, a second cloud or an exit enters the picture, the file in the repository is the only part of the answer that travels.
Copilot Studio and Google AI Studio questions
The four answers buyers ask for first, then two that follow.
Yes. Gemini Enterprise is Google's counterpart, and its build layer is the Gemini Enterprise platform, with Agent Studio and the Agent Development Kit. Google AI Studio is not a Copilot Studio equivalent: it is a prompt-to-app playground and an API key.
Kortix is the one to start with, because the agent definition is a file in your own repository. Gemini Enterprise is the alternative when you are buying Google Cloud. Both beat a second studio you rent, if the definition is what you want to keep.
Yes, with a condition. Microsoft charges nothing for the Copilot Studio account a maker uses, but you need a tenant prepaid Copilot Credit pack subscription before you can get it. The trial account works, and it cannot publish an agent.
They are different products, so one is not a better version of the other. Copilot Studio builds agents. Microsoft 365 Copilot is the assistant people already use, and agents from the studio can publish into it. Kortix builds agents you own.
Not as files. An agent is a set of records in a Power Platform environment, so a move means rebuilding it against another runtime. Starting from a markdown file and a manifest makes that move a clone instead.
The builder now sits inside the Gemini Enterprise platform. Google's agent-builder URL serves that platform's page, where Agent Studio, the Agent Development Kit and Model Garden are the building tools.
Own the agent definition, wherever it runs
Agents, skills, memory and connectors in one git repo, running where you put them.