Instacode
An AI coding agent for IntelliJ, Visual Studio, VS Code and the browser that edits files, runs commands and searches your code, with a person approving every risky step. It works with whichever models the company chooses.
- Coding agent
- Autocomplete
- IDE plugins
- MCP
- Model-agnostic
01
Overview
Insta Code is a coding agent that runs inside the IDE or in a browser workspace. In the IDE it works on the developer's own project; in the browser each project gets its own Docker sandbox. The agent reads and edits files, runs commands, searches code by meaning through a Qdrant index, and uses MCP servers, skills and project rules.
- Category
- AI coding agent
- Industries
- Enterprise · Banking & finance
02 · Business value
What it changes for the business
Instacode
Developers finish routine work faster with an agent the company controls: its models, its approvals and its budget.
- 01
Faster routine development
Edits, searches, commands and completions happen inside the editor the developer already uses.
- 02
Code stays under company control
Any OpenAI-compatible endpoint can be connected, so code goes only to models the company hosts or approves.
- 03
Lower operational risk
Approvals, blocked commands and secret detection stop the agent from making unreviewed changes or exposing credentials.
- 04
Predictable AI spend
Token quotas per user and team, and routing turns to smaller models, keep model costs visible and capped.
03 · The Problem → The Outcome
Challenges → Solutions
- 01
Challenges: Developers lose time on boilerplate, code searches and routine edits
Solutions: The agent edits files, runs commands and searches the project, and autocomplete suggests code as you type
- 02
Challenges: Public AI coding tools send code to services the company does not control
Solutions: Admins connect any OpenAI-compatible endpoint, including models the company hosts itself
- 03
Challenges: An agent that can run commands can also break things or leak credentials
Solutions: Risky tool calls need approval, blocked commands never run, and calls that touch secrets always ask
- 04
Challenges: Teams work in different IDEs, so one tool rarely fits everyone
Solutions: One shared core powers IntelliJ, Visual Studio, VS Code and a browser workspace with a Docker sandbox
- 05
Challenges: AI usage costs are hard to see and cap across many developers
Solutions: Every model call is recorded, with token quotas per user and team
04 · Use cases
Where it fits, by industry
Enterprise
Scalable AI solutions for large organizations.
- 01
In-house coding assistant
Platform teams roll out one agent across IntelliJ, Visual Studio and VS Code, connected to the company's approved models.
- 02
Browser workspaces for quick builds
Developers build and test small apps in a sandboxed browser workspace, without installing anything on their machine.
Banking & finance
Compliant AI solutions for banks and financial institutions.
- 01
Controlled AI for regulated codebases
Teams that cannot send code to public tools run the agent on internal models, with approvals on every change and a record of every model call.
05
Enterprise Capabilities
Intended Users
Software developers working in their IDE or the browser, and platform admins who manage models, users and quotas.
Instacode
AI coding agent
- 01Agent and chat modes with tool approvals
- 02Inline code completion
- 03Semantic code search
- 04MCP servers, skills and project rules
- 05Per-project memory
- 06Model routing and usage quotas
06 · Highlights
Key Proof Point
Instacode
One shared core runs the agent's file, search and shell tools in IntelliJ, Visual Studio, VS Code and the browser sandbox, with a human approval on every risky call.
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