Smart Routing
Calibrated confidence scoring across 12 providers and 40+ models. Each task goes to the model with the strongest track record for that task type.
Describe what you need. a21e picks the right model from 12 providers, applies your context and memory, runs quality gates — and delivers expert results in seconds.
Review this PR for security vulnerabilities. Flag injection risks, auth gaps, and unsafe deserialization.
Intent Analysis
4 constraints extracted
Smart Routing
Claude Sonnet 4 via Anthropic
Memory
12 preferences applied
Quality Gate
94 / 100
2 issues — SQL injection, missing auth check
1 safe — deserialization validated
Quality
94
Say what you need in plain English. We'll add the structure, the guardrails, and the precision — so your AI hears exactly what you mean.
Run a real task through the pipeline — intent analysis, routing, memory, quality gates — and see the output.
Task
Write a cold email targeting SaaS CTOs with 50–200 engineers. Keep it under 150 words, peer-level tone, and end with a specific low-commitment CTA.
2,000+
Reference prompts
15
Autonomous agents
12
LLM providers
40+
Models supported
6
SDKs
$5
To get started
How it works
Getting good output from AI requires the right prompt, the right model, the right context, and a quality check at the end. That's four jobs. a21e does all four — so your only job is knowing what you want.
Type what you need in plain language. The intent engine extracts task type, audience, constraints, and success criteria.
Six memory types — facts, preferences, corrections, project context, voice, and domain knowledge — are applied before anything runs.
The engine builds a bespoke prompt from 2,000+ reference patterns, tuned for your task and context. No template selection — fresh synthesis every time.
Calibrated routing scores 12 providers across 40+ models and picks the one with the strongest track record for your task type.
The synthesized prompt goes to the selected provider. Response streams back in real time. Credits are deducted based on actual token usage.
Every output is scored against eight quality criteria. Below threshold, the engine retries with a different approach. Scores feed forward to improve the next run.
The platform
Calibrated confidence scoring across 12 providers and 40+ models. Each task goes to the model with the strongest track record for that task type.
Facts, decisions, corrections, project context, voice, and domain knowledge — six memory types that persist across sessions and inform every execution.
Eight-criteria scoring on every output. Below threshold, the engine retries with a different approach. Scores feed back into future synthesis.
Multiple LLMs propose plans, cross-critique, and reach consensus via Condorcet/Schulze voting. Reduces single-model hallucination on high-stakes decisions.
Sandboxed, signed extensions that give your AI new capabilities. Install once, execute anywhere. Full audit trail on every invocation.
Extract abstract design tokens from any URL — colors, typography, spacing, shadows. Apply brand voice to every output. 5 credits per extraction.
Severity-ranked findings with file-level guidance. Turn review findings into agent tasks that generate fixes and open a PR.
Three or more models propose, critique, and vote. Pairwise comparison matrices and posterior win probability surface the strongest plan.
15 purpose-built agents for code, tests, security, CI, docs, and analysis. Three autonomy modes: supervised, balanced, autonomous.
Audit any codebase against 19+ automated engineering guards. No-any, no-suppression, no-deferred-placeholders, ESM-only, and more.
Intent-first workspace for complex decisions. Type what you need, get a structured execution with conversation history, consensus rounds, and deliverables.
Purpose-built workflows for websites, code reviews, StylePrints, agents, consensus planning, CI remediation, and project governance.
Autonomous agents
Each agent handles a specific task — from writing code to fixing CI failures to generating compliance documentation. Quality gates enforce minimum output standards. Credit caps prevent runaway costs. Three autonomy modes let you decide how much control to keep.
GitHub Coding, Refactoring, Performance, Accessibility
Write, refactor, and optimize code with autonomous PRs.
Test Generator, API Contract Tests
Generate unit, integration, and contract tests that cover edge cases.
Security Auditor, Security Hardening
Scan for vulnerabilities. Then fix them.
CI Failure Fix, Dependency Upgrader, Observability
Diagnose CI failures, upgrade dependencies, add instrumentation.
Docs Generator, Database Migration
Generate docs from code and plan safe schema migrations.
Codebase Analysis, Code Review Fixer
Deep architecture analysis and automated review fixes.
Three autonomy modes: supervised, balanced, autonomous. You set the guardrails.
See it in action
Every example below was generated by the a21e pipeline — intent analysis, context enrichment, prompt synthesis, smart routing, and quality gates.
Code Review
“Review this PR for security vulnerabilities”
Sales Email
“Cold email targeting SaaS CTOs, 50–200 engineers”
Financial Analysis
“Q4 performance summary with variance analysis”
Architecture Decision
“Evaluate event sourcing vs. CRUD for order system”
Try it yourself — $5 gets you started with real tasks on real models.
What teams say
“a21e cut our prompt engineering time by 80%. We describe what we need and the platform handles the rest.”
15 autonomous agents write code, generate tests, fix CI failures, audit security, and open PRs — with quality gates, credit caps, and rollback on failure. OpenAI-compatible API: change one URL and your existing code gains routing, memory, and quality gates.
Learn moreDiscovery call prep in minutes, not hours. Campaign copy that matches your brand voice because Memory and StylePrint persist your tone, terminology, and style. Quality gates catch off-brand output before it ships.
Learn moreShared memory, workspace policies, and usage controls. Every team member gets expert AI output while leadership maintains governance. Decision records capture what was decided, why, and by which models.
Learn moreAES-256-GCM encryption at rest, TLS 1.3 in transit. Full audit trail on every execution with user attribution and model details. Compliance dashboard with 19 trackable items across must-do, should-do, and nice-to-have categories.
Learn moreFinancial modeling, risk assessment, and compliance documentation — structured for spreadsheets, slide decks, and audit trails. Quality gates verify numerical consistency. Assumptions are explicit, not buried.
Learn moreFive feedback loops run after every execution: intent clustering learns which techniques work for your kind of task, memory-informed selection adjusts weights from your signals, provider tuning shapes output per model, failure exemplars show the engine what not to repeat, and quality scores feed forward into the next run.
The engine tracks which technique combinations produce the highest quality for each task type and industry. Your runs inform better synthesis for similar tasks.
When output scores low, the engine captures what went wrong and feeds it back as a negative example. The same failure pattern is excluded from future synthesis.
Routing confidence is calibrated using isotonic regression on historical outcomes. Each provider-model pair builds a track record that informs future selections.
Every run makes the next one better. Your context compounds, your quality climbs, and the platform learns what works for you.
ChatGPT is a chat interface. a21e is an execution platform: 15 autonomous agents, multi-model deliberation, quality gates, and persistent memory behind every task.
AES-256-GCM encryption at rest, TLS 1.3 in transit. Provider keys decrypted only during execution, never logged. Full audit trail on every run.
$5 to try. No subscription. No commitment.
Yes. Bring your own keys for any of our 12 providers and pay lower platform fees. Your keys are encrypted with AES-256-GCM and decrypted only during execution.
VS Code extension with IntelliSense. CLI with device authorization. MCP integration for any compatible coding assistant. Or just use the API.
Our OpenAI-compatible shim means you can point your existing code at a21e by changing one URL. Same SDK, same format — plus routing, memory, and quality gates.
Pick a task type, pick a model tier, and see a realistic credit range.
Test
$5
One-time credit pack to run real tasks.
Pro
from $129
Full execution layer with agents, API access, and unlimited keys.
Enterprise
Contact
SSO, audit trails, data residency, and dedicated support.
One credit pack. 15 agents. 12 providers. Quality gates on every output. See what happens when your AI has real infrastructure behind it.