AI agents that improve themselves.
One runtime. 39 models. 13 squads. Real tool execution. Self-improving routing.
The Problem
AI agents fail in production because the infrastructure doesn't exist.
Single-model fragility
One provider goes down, your system crashes. No fallback chains, no routing intelligence, no resilience.
No self-improvement
Models degrade silently. No shadow testing, no quality scoring, no auto-promotion. You find out when users leave.
Security as afterthought
Jailbreaks, PII leaks, prompt injection โ discovered in production. Not enforced at the infrastructure layer.
Our Product
Autonomous Agent Runtime
The complete platform for building, deploying, and operating AI agents at scale. Every feature works. Every model is real. Every tool executes.
Multi-model orchestration
13 specialized squads route every request to the optimal model. Claude, GPT, Gemini, DeepSeek, Grok, Qwen, Mistral, Nemotron, MiniMax โ all competing, all with fallback chains, all quality-scored.
Web search, code execution, image generation, TTS, file reading โ 11 tools that actually execute, not UI checkboxes.
Query 7 frontier models simultaneously. See Claude vs GPT vs Gemini side-by-side on the same prompt.
Architecture
Four pillars. One runtime.
Zeus
Routing Intelligence
Intent classification across 10 categories. 13 specialized squads. Budget-aware model selection. Quality-based re-routing with cyclic fallback. Conditional routing graph.
Forge
Agent Factory
Natural language to agent swarm. Domain parsing with schema validation. Topology generation. AuraGen adversarial testing (10 parallel tests). Manifest compilation and Zeus registration.
Darwin
Self-Improvement
Live trace capture on every request. Background judges scoring quality. 5% shadow testing with challenger models. Auto-promotion when challengers outperform. The system gets better without engineers.
Guardian
Security Enforcement
3-layer inline defense. Layer 1: 30 jailbreak patterns + PII auto-redaction (0ms). Layer 2: GPT-5-nano adversarial classifier (parallel). Layer 3: Output scanning. 8-rule policy engine. Tool whitelist per squad.
How It Works
Three steps. Every request.
Route
Guardian scans input in 0ms. Intent classifier picks the best squad. Budget-aware model selection with 28 fallback chains.
Execute
Squad calls the optimal model with real tools. Web search, code execution, image generation. Token-by-token streaming.
Improve
Darwin traces every decision. Background judges score quality. Shadow tests challengers. Auto-promotes winners. Zero human intervention.
Developer SDK
Five lines to production AI.
Install @mifal/sdk, pass your API key, stream multi-agent responses with tool execution.
npm install @mifal/sdkimport { MifalClient } from "@mifal/sdk";
const mifal = new MifalClient({
apiKey: "mfk_your_key_here"
});
const stream = await mifal.chat.stream({
message: "Search for latest AI news",
mode: "FAST"
});
for await (const event of stream) {
if (event.type === "token")
process.stdout.write(event.text);
if (event.type === "tool_call")
console.log("Tool:", event.tool);
}Pricing
Start free. Scale with confidence.
Developer
For builders exploring MIFAL
- + 1,000 requests/month
- + FAST mode
- + 3 squads
- + Web search + calculate
- + Community support
Team
For teams shipping AI products
- + 50,000 requests/month
- + All modes (FAST/ACCURATE/PRO)
- + All 13 squads
- + All 11 tools
- + Compare + Research mode
- + Priority support
Enterprise
For organizations at scale
- + Unlimited requests
- + Dedicated infrastructure
- + Custom model routing
- + SLA guarantee
- + Defense/government ready
- + Dedicated support engineer
Vision
The operating system for AI agents.
Today, every company building with AI is reinventing the same infrastructure โ model routing, fallback chains, security scanning, quality monitoring, tool execution. They build it poorly, maintain it painfully, and it breaks in production.
MIFAL is the answer. A single runtime that handles all of it โ so teams can focus on what their agents do, not how they run. We believe the future isn't more models. It's better infrastructure for the models we already have.
Our north star: every AI agent in production runs on Vezran infrastructure. The routing layer, the security layer, the improvement layer โ invisible, reliable, self-improving. Like AWS for compute, but for AI agent orchestration.
Multi-model agent runtime
39 models, 13 squads, real tool execution, self-improving routing. Live at mifal.vezran.ai.
Enterprise agent deployment
Custom agent swarms compiled from natural language. One-click deployment. SOC 2 certified.
Autonomous agent marketplace
Publish, share, and monetize agent swarms. Cross-organization agent collaboration. The AWS Marketplace for AI agents.
Ready to see it live?
39 models. 13 squads. Real tool execution. Self-improving. Try it now.