Introducing PyraFlow: Not a Chatbot. A Workforce.

You already know how to use Claude. You've probably tried building agents with ChatGPT. Maybe you've looked at self-hosting OpenClaw. Here's why we built PyraFlow anyway — and why it's different.

The Problem With Chat Windows

Claude and ChatGPT are brilliant — when you're sitting in front of them. Close the tab and they forget you exist. They can't post to TikTok, generate video, check your email, or remember what worked last week. They're tools you operate, not agents that work for you.

3x Cheaper Than Self-Hosting

When you self-host, you typically run one model for everything — premium reasoning for tasks that don't need it.

PyraFlow uses smart model routing to match every task to the right price tier automatically. Creative work gets the best model. Background tasks, memory, and validation get routed to faster, cheaper alternatives. You don't configure this — it just happens.

Combined with session optimization and context compression, this adds up to roughly 3x lower cost on autonomous operations compared to single-model self-hosting.

2x Media Production Efficiency

Your team writes 100-200 word prompts describing what things look like. That's the #1 failure mode — text descriptions override reference images in models like Kling and Nano Banana.

PyraFlow's AI writes 20-40 word prompts focused purely on motion and camera direction. Then a separate AI validates the output across 5 dimensions (identity consistency, physical plausibility, motion quality, temporal consistency, prompt alignment) and auto-retries with targeted improvement suggestions.

Result: 60% fewer wasted generations. Your agent produces more usable content per credit than a human prompt engineer.

Zero Prompts to Write

You bring the idea and the references. Your agent handles:

• Prompt engineering optimized for each specific model (Kling, Nano Banana, Seedance)
• Negative prompts that are context-aware (people vs products vs physical actions)
• CFG scale tuning based on motion complexity
• Quality validation before delivery
• Auto-retry with improvement suggestions when quality falls below threshold

No prompt writing. No trial and error. No wasted credits on bad outputs.

Brand Consistency at Scale

Consistent Elements are named, versioned bundles of reference images — characters, products, brands — that persist across all content generation. Say "create a video featuring Nathan holding the Rose Gold Ring" and your agent resolves both elements by name, passes structured references to the generation model, and chains frames sequentially for visual consistency.

50 pieces of content featuring the same product. Zero manual re-uploading. Zero visual drift.

Agents That Get Better Over Time

Not conversation history — structured semantic memory. Your agent extracts facts from every interaction, deduplicates them, and recalls relevant context via semantic search. When a learning recurs 3+ times, it gets promoted into the agent's operating instructions.

Your agent literally rewrites its own playbook based on experience. It tracks its own errors, extracts successful workflow patterns, and applies them automatically next time.

Real Work, Real Integrations

Not toy plugins. Your agents hold encrypted OAuth credentials for 15+ services and actually use them during autonomous work cycles:

• TikTok, Instagram, YouTube — publish videos, engage comments, track analytics
• Gmail, Slack, Lark — read messages, send replies, post updates
• Stripe, Plaid — check revenue, track transactions
• GitHub — scan issues, review PRs, search code
• Ayrshare, Buffer, Publer — schedule posts across platforms

All running on configurable heartbeat schedules (10 minutes to 4 hours) while you sleep.

Get Started

PyraFlow is in beta with a 14-day free trial on all plans. Deploy your first agent in minutes — not months of infrastructure setup.