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Flagship product by WebReinvent AI Software Factory

The Keyboard Era Is Over.The AI Agent Era Has Arrived.

Q: How does VaahAgents execute tasks?

Each task runs a sequence of prompts on a persistent Claude Code session. You can execute the next pending task one at a time, or fan out all executable tasks in parallel - the platform handles the ordering and keeps every run isolated.

Q: Which CLI or provider does VaahAgents use?

It's built around the Claude Code CLI. The providers - the model and CLI backends agents run on - are configurable, so you point agents at the provider and credentials you already use.

Q: How does VaahAgents keep agent work isolated?

Each project maps to a codebase - a git repository. Every run happens in its own git worktree, so parallel agents and tasks work on different files and branches without colliding.

Q: Can I run multiple agents or tasks at the same time?

Yes. Because every task runs in its own git worktree, you can execute all pending tasks in parallel and run multiple agents at once without them stepping on each other.

Q: What happens when a task finishes?

The agent's work lands as a diff you can review and merge - it can open a merge request against your repo, with GitLab supported via your GitLab token and SSH keys. Nothing is applied silently.

Q: What are workflows in VaahAgents?

A workflow is an ordered list of agents that run in sequence, so you can chain several agents together for multi-step, multi-agent jobs - each agent handing off to the next.

Q: Do agents remember context between runs?

Yes. Each agent keeps its own memory per project, so it carries context from previous runs instead of starting from scratch every time.

Q: How do I connect a repository?

Register a codebase - your git repo - create a project that points to it, and add your credentials (a GitLab token and/or SSH keys) so agents can clone, work, and open merge requests.

Q: Is VaahAgents part of a bigger ecosystem?

Yes. VaahAgents is the agentic layer of the Vaah.AI ecosystem, alongside LLM KB (the knowledge base) and GenicUI (the protocol that lets agents use your UI). The platform is self-contained and deploys with Docker Compose.

Bypass traditional SDLC bottlenecks by assigning VaahAgents to every stage. Connect codebase to a project, map tasks across your trusted providers, and chain them into an automated workflow. Watch live executions run on an isolated branch-streaming steps, committing code, and handing off work in real time.

Open Source Documentation

VaahAgents

Plan & Research

Mapping requirements & scope

#Agent 1

Gather requirements
Analyze the codebase
Break work into tasks
Map the agent workflow

Design

Architecting the solution

#Agent 2

Understand requirements
Generate design concepts
Refine architecture
Deliver final designs

Development

Building and implementing

#Agent 3

Set up project structure
Implement core features
Refactor and optimize
Commit the changes

Deployment & Testing

Testing and shipping

#Agent 4

Run automated tests
Fix failing checks
Deploy to environment
Verify in production

Where Humans Stop Chattingand Agents Start Building

Fast, AI-driven code generation

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      [arr] <= 1:
    sreturn arr

pivot = arr[0]
left = [x for x in arr[1:]
if x < pivot]
right = [x for x in arr[1:]
if x >= pivot]

return quick_sort(left) +
[pivot] + quick_sort(right)

VaahAgents

Structured Step Execution

// place the frame in the current window
window::Current->Content = rootFrame;
Window::
//Ensure
Window::
}, task_co
}
else

Closed

Content

CoreWindow

Scaffolding

Fast project setup

1. {
2. "product": {
3.    }
4.    "product_name":
5.    "price" : $48.00
6.    },
7.    {
8.    "product_name":
9.    "price" : $48.00
10.   }

Code Review & Audit

AI-powered feedback

Integrate

Multiple AI Models

How VaahAgents Works

Six steps from your codebase to a shipped pull request - set it up once, then watch your agents carry the work.

Connect your code

Create a Project and bind it to a Codebase - a git repo or a local folder. VaahAgents clones it into an isolated worktree, so every agent execution runs on its own branch in a clean, separated environment.

Wire Providers & Agents

Add the Providers you already use - Claude Code, Codex, OpenAI, Gemini - then configure the Agents that use them: system prompt, token budget, timeout, allowed tools, and retry policy. Each agent is set to autonomous mode for workflow execution or interactive mode for chat and planning.

Compose a Workflow

Order your agents into a Workflow - a linear chain with position-based ordering. Each agent picks up where the last one left off via context handoff, and the runtime injects an AI Workflow section into every agent's system prompt so it knows where it sits in the chain and what the earlier agents finished.

Plan Tasks

Add Tasks - the units of work for the project. Break a feature, a refactor, or a bug fix into clear tasks with a title, details, and an assigned workflow. Project Memory carries durable facts (frameworks, conventions, key files) across sessions, so the next task starts with full context instead of re-gathering the same requirements.

Execute the Workflow

Hit Execute - or Execute All to fan out tasks in parallel. The LangGraph engine dispatches each agent in its own worktree, and in production, its own Docker container bounded by cgroup memory and CPU caps. Every step streams in real time over SSE: tool calls, stdout, agent start/end, and progress counters. Cancel mid-run and every in-flight coroutine is torn down cleanly.

Review & ship

When a task's workflow finishes with status done, Auto-PR pushes the worktree branch through the Forge layer - GitHub, GitLab, or CLI fallback - and opens or updates a Pull Request. Six PR fields are persisted on the execution record so you can track them from the UI. Project Memory carries forward, so your next round of planning starts with the full context already in place.

AI Agents vs. Traditional SDLC - The Faster Way to Ship

Legacy SDLC scales with headcount and stalls at every handoff - VaahAgents scales with agents and ships in hours.

The Vaah Way

VaahAgents

The Old Way

Legacy SDLC

Ship faster

AI agents work the task continuously and in parallel - delivery drops from weeks to hours/days

Slow to ship

Features take weeks or months, with handoffs between teams

Scale without headcount

A small team orchestrates many agents, and output scales without new headcount

Expensive teams

Output only scales if you hire more people

Automated busywork

Agents handle the repetitive execution; humans set direction and review

Repetitive manual work

Boilerplate, testing, and deployments eat hours

Knowledge that compounds

Capabilities are captured as reusable agents & workflows - institutional, not tribal

Knowledge silos

Expertise lives in a few people's heads

Seamless handoffs

One task flows through a defined agent workflow - fewer handoffs, less rework

Lost in handoffs

Requirements get distorted across PM → design → dev → QA

Consistent quality

Consistent agent-driven checks run as part of every workflow

Bugs & tech debt

Manual testing misses things

Live visibility

Real-time view of every step, with the power to start, stop, or cancel runs

No live visibility

You learn the real status at the end, not during

Adapts fast

Adjust and re-run the workflow fast

Rigid to change

Mid-project changes are slow and costly

What Sets VaahAgents
Apart from Others

Intelligent by design. Powerful in action.

Autonomous Intelligence

Agents make smart, proactive decisions, no manual input needed.

Multi-Provider Support

Seamlessly run Claude, OpenAI, and Gemini together in a single workspace.

Live Progress Streaming

Watch your AI team think, call tools, and complete steps live as it happens.

Multi-Agent workflows

Link specialized agents into assembly lines that tackle complex end-to-end tasks as one team.

Built-In Guardrails and Security

Every task runs in an isolated worktree under strict tool guardrails, keeping execution safe and your data fully yours.

Organized Task Tracking

Keep your codebase, task queues, and shared context perfectly organized in a single dashboard.

Where VaahAgents Makes the Biggest Impact

Built for every team that ships software - from two-person startups to regulated enterprises.

Software & SaaS

Ship more features with the same team - scale output without scaling headcount.

Enterprise & Legacy Modernization

Tackle big migrations and modernization as controlled, step-by-step agent workflows.

E-commerce & Retail

Rapid feature rollout and experimentation without bottlenecking engineering.

Fintech & Banking

Fast iteration with an auditable, governed trail on every line of code.

IT Services & Consultancies

Deliver client projects faster and scale delivery without hiring more engineers.

Healthcare & Healthtech

Quality-critical, regulated code - with verifiable, reviewable outcomes.

Explore the Powerful
Capabilities of VaahAgents

Agents that work on your code, stream every move in real time, and leave a record of everything they did.

Plan

Code

Test

Execute

Live

Multi-Agent Workflow Engine

Chain AI agents to build, test, and execute code in real time using LangGraph and live SSE streaming.

CPU

TIME

CONTEXT

SANDBOX

✦ Agent Process

Isolated

Safe
Environment

Isolated Subprocess Control

Run tasks safely in sandboxed environments with hard budget caps, timeouts, and full project context.

ClaudeLLM

OpenAILLM

GeminiLLM

Custom LLMAPI

VaahAgentsROUTER

Any Model Orchestration

Connect any LLM provider like Claude, OpenAI, or Gemini. Get coordinated, reliable workflow execution every time.

What You Can Build with VaahAgents

Explore how autonomous AI agents execute real-world developer tasks directly on your codebase.

Building New Features

Turn plain English prompts into working code changes across your entire project.

Code Reviews

Catch bugs, security risks, and messy code automatically before you commit.

Fixing Bugs Fast

Feed error logs to the agent to find root causes and generate instant bug fixes.

Upgrading & Cleanup

Multi-file code refactoring and seamless framework migrations.

Comparing AI Models

Test the exact same prompt across Claude, OpenAI, and Gemini to see which gives the best result.

Writing Project Docs

Keep READMEs and API docs in sync automatically as your codebase keeps evolving.

Building New Features

Turn plain English prompts into working code changes across your entire project.

Code Reviews

Catch bugs, security risks, and messy code automatically before you commit.

Fixing Bugs Fast

Feed error logs to the agent to find root causes and generate instant bug fixes.

Upgrading & Cleanup

Multi-file code refactoring and seamless framework migrations.

Comparing AI Models

Test the exact same prompt across Claude, OpenAI, and Gemini to see which gives the best result.

Writing Project Docs

Keep READMEs and API docs in sync automatically as your codebase keeps evolving.

Why Choose VaahAgents?

Run autonomous AI workflows directly on your codebase with live updates and total control.

Subprocess IsolationSmart GuardrailsMulti-Model NativeLangGraph EngineVector MemoryAgent OrchestrationReal-Time StreamingProject Workspaces100% Data OwnershipAutomated QueuesWorkflow Builder

Why Choose VaahAgents?

Run autonomous AI workflows directly on your codebase with live updates and total control.

Subprocess IsolationSmart GuardrailsMulti-Model NativeLangGraph EngineVector MemoryAgent OrchestrationReal-Time StreamingProject Workspaces100% Data OwnershipAutomated QueuesWorkflow Builder

Frequently, asked questions

The questions we hear most before a team starts orchestrating agents.

What is VaahAgents?

VaahAgents is WebReinvent's AI agent orchestration platform. You break work into discrete tasks, and agents execute them by running prompts sequentially via the Claude Code CLI - each in its own git worktree - and open a merge request when the work is done.

How does VaahAgents execute tasks?

Which CLI or provider does VaahAgents use?

How does VaahAgents keep agent work isolated?

Can I run multiple agents or tasks at the same time?

What happens when a task finishes?

What are workflows in VaahAgents?

Do agents remember context between runs?

How do I connect a repository?

Is VaahAgents part of a bigger ecosystem?

100+

Trained IT
Professionals

Faster Assembly
Velocity