Stop AI Hallucinations Before They Start
Run models from OpenAI, Google, Anthropic, xAI, Perplexity, and OpenRouter in parallel. They check each other's work, debate solutions, and catch errors before you see them.
Core Capabilities
Built for developers who need reliable AI reasoning
Parallel Verification
Run multiple models simultaneously from OpenAI, Google, Anthropic, xAI, Perplexity, and OpenRouter. They vote on answers and cross-check each other's work in parallel.
simultaneous executionLive Fact-Checking
Perplexity and Grok search the web in real-time for the latest information (past week). Get verified answers with actual sources, not hallucinated citations.
real-time searchMulti-Round Debates
Make models argue for 3-200 rounds to refine solutions. Competitive mode (challenge each other), collaborative mode (build together), or debate mode (structured discussion).
3-200 roundsAdversarial Challenge
Built-in challenger tool finds logical flaws, pokes holes in reasoning, and prevents echo chambers. Bad answers get caught before you see them.
error preventionConfigurable Tools
Turn tools on/off in tools.config.json. Need just 1 tool? Use 400 tokens overhead. Want all 31 tools? Use 13k tokens. You control costs and context usage.
400-13k tokensCustom Workflows
Chain unlimited steps with YAML/JSON config. Pass outputs between steps, run models in parallel, branch conditionally. Works best with Claude Code MCP integration.
unlimited stepsHow It Reduces Hallucinations
Run multiple AI models on the same question. They check each other's answers, debate solutions, and catch mistakes before you see them.
Based on peer-reviewed research (arXiv:2406.04692)
The Problem
A single AI model can confidently give you wrong answers. It doesn't know when it's making things up.
What TachiBot Does
TachiBot runs your question through multiple models at once. They generate answers independently, then review each other's work to catch mistakes.
Why This Works
Researchers tested this approach and published the results. When models check each other, hallucinations drop significantly.
The AI your AI calls for help.
Real GPT-5 to GPT-5.1 migration analysis with 5 AI models
Real Example: Deep Research with Verification
Stop Trusting. Start Verifying.
Single Model
"What breaking changes are in React 19?"TachiBot
"What breaking changes are in React 19?"Models challenge each other (3-200 rounds)
Search live sources with recency filters
Why You Need This
AI makes stuff up. One model gives you confident wrong answers. You waste hours debugging hallucinations.
Token costs eat your budget. Every tool loaded costs tokens. 31 tools = thousands of tokens per request before you even start.
You're stuck with rigid workflows. Want to verify an API with 3 different models? Build a custom 40-step process? Too bad.
One model isn't enough. Complex problems need multiple perspectives. But coordinating models manually is painful.
What You Get
AI models check each other. Perplexity researches, Grok verifies, Challenger pokes holes. Bad answers get caught before you see them.
You control token costs. Need 1 tool? Use 400 tokens. Need all 25? Use 13k. Turn tools on/off in one config file.
Build any workflow you want. YAML/JSON config. Chain unlimited steps. Customize parameters. Make models debate for 200 rounds if you want. Have fun.
Models work together. Multiple AI models brainstorm, build on ideas, and synthesize better solutions than any single model can produce.
Works With Leading AI Providers
Always using the latest models from each provider
Works best with Claude Code MCP integration
Customize Everything
Control token costs and build custom workflows with simple config files
Profile System
Toggle tools on/off to control token usage
Choose a preset profile or create your own. Toggle individual tools on/off to control exactly which capabilities load and how many tokens you use.
{
"customProfile": {
"enabled": true, // ← Use custom profile
"tools": {
// Research tools
"perplexity_ask": true, // ✓ ON
"scout": true, // ✓ ON
// Reasoning tools
"grok_reason": true, // ✓ ON
"challenger": true, // ✓ ON
"verifier": true, // ✓ ON
// Creative tools
"openai_brainstorm": true, // ✓ ON
"gemini_analyze_code": false, // ✗ OFF
"qwen_coder": false // ✗ OFF
}
}
}Optimize your context. Tools take token space. Load only what you need. Switch profiles anytime.
Custom Workflows
Write your own multi-step AI workflows
Define custom workflows in YAML or JSON. Chain any tools together, pass outputs between steps, run models in parallel. This example runs 4 models simultaneously, synchronizes their perspectives, then debates to refine the solution.
# Real workflow from TachiBot
steps:
# Step 1: 4 models run in parallel
- tool: gemini_brainstorm
output: creative_view
- tool: openai_brainstorm
output: systematic_view
- tool: perplexity_ask
output: research_facts
- tool: qwen_coder
output: technical_view
# Step 2: Synchronize perspectives
- tool: think
params:
thought: "Combine all perspectives"
output: sync
# Step 3: Debate to refine
- tool: focus
params:
mode: "deep-reasoning"
rounds: 5
output: refinedBuild your own workflows. Create unlimited variations. Save as .yaml or .json files. Run with workflow(name: "swarm-think")
Get Started in Minutes
Add to Claude Desktop or any MCP client
# 1. Install via npm
npm install -g tachibot-mcp
# 2. Add to Claude Desktop config
# ~/.config/Claude/claude_desktop_config.json
{
"mcpServers": {
"tachibot": {
"command": "tachibot-mcp",
"args": ["--config", "~/.tachibot/config.json"]
}
}
}
# 3. Configure API keys (optional)
{
"apiKeys": {
"openai": "sk-...",
"gemini": "...",
"perplexity": "..."
}
}
# 4. Start using!
tachibot workflow run swarm-think "Your query here"