Before Convilyn was a workflow platform, it was a keyboard. This is how a simple belief — that AI should be frictionless for everyone, not just power users — led us to rethink everything twice, and why that conviction still drives every decision we make.
The two-sided platform vision — where users with problems and developers who can solve them find each other on a shared, stable architecture.
Two products, one vision. How the workflow foundation we build today becomes the intelligence layer for a much simpler AI experience tomorrow.
Real scenarios: upstream trigger → workflow → downstream result
Upload your resume. The AI analyzes it, suggests job directions, and generates tailored resumes + an application tracker for each.
Upload your resume and the JD — the agent extracts requirements and writes a cover letter that speaks directly to the role.
Resume + job description in → role-specific question bank, model answer frameworks, and skills gap analysis out.
Saw something inspiring? Got told to "make it social"? Upload the source doc — get platform-ready content for every channel.
Upload any contract — get a clause-by-clause analysis with risk scoring and obligation summaries before the signing deadline.
Upload any notes file — the agent extracts key concepts into Q&A pairs organized by topic. Study smarter, not longer.
Upload a lecture or tutorial video — get timestamped study notes with key concepts, summaries, and review questions automatically.
Your boss forwarded a thread and said "handle this." Upload the context documents — get a ready-to-send email draft with the right tone.
Upload a stack of invoice PDFs — line items, tax, and totals extracted into an accounting-ready spreadsheet. No re-entry.
Upload your images or brief — get 3–5 platform-ready post variations for Instagram, LinkedIn, and X with captions and hashtags.
Step-by-step guides for users and developers
A step-by-step guide to fast-track format conversion — image, document, PDF, OCR, video transcription, and more.
From uploading a file and selecting a workflow, through interactive checkpoints, to downloading your finished output. Walkthrough with AI Job Search Assistant.
Authentication, job creation, slot filling, interactive checkpoints, polling, and result download — everything needed to embed workflows in your app.
Before Convilyn was a workflow platform, it was a keyboard — a vision for frictionless AI for everyday people, not just power users.
Our vision for a two-sided platform where users with problems and developers who can solve them find each other on a shared, stable architecture.
Every Convilyn workflow starts and ends with a file. That's not a limitation — it's the design principle that keeps AI focused, measurable, and composable.
Two products, one strategy. How proven AI workflows become the intelligence layer for a much simpler, more embedded everyday experience.
Why Convilyn splits into two completely separate execution paths — and why a unified pipeline would have made both worse.
How Goal Lane models agent execution as a 5-node graph with conditional routing — reason, call_tool, request_input, nudge, and finish.
How JSON spec files define nearly 100 distinct AI workflows without any new agent code — schema, preflight validation, and spec versioning.
Capability-based MCP servers, the six file argument strategies, reference IDs for binary tool outputs, and the three control-flow tools.
One template drives nearly 100 workflows. The decision framework for when to write a 351-line specialized prompt instead — and why.
The threshold formula that switches the LLM from mandatory tool invocation to autonomous reasoning — and why control-flow tools are excluded.
How the agent manages 120-iteration conversation history — the trimming strategy, what gets preserved vs discarded, and the history loss bug we fixed.
The formula max(100K, max_iterations × 10K) — why a fixed budget fails at both ends, and how it interacts with the iteration limit.
Six event types, milestone-based progress calculation vs iteration fallback, connection recovery via event IDs, and the progress reporter protocol.
A 2-tier testing framework: lifecycle compliance (does the workflow complete correctly?) and goal-oriented content validation (does the output achieve its purpose?).
10 real-world scenarios — each one walks from the upstream trigger through Convilyn tools to the downstream deliverable, so you can see exactly where we fit.
Browse all playbooksNearly 100 AI workflows. Two lanes — Turbo for instant format conversion, Goal for multi-step intelligent processing. Free tier, no credit card required.
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