WeYala spins up a crew of specialist AI agents — researchers, business planners, technical architects, BD operators, code writers, security reviewers — that execute autonomously in the background. You stay in command through approval gates at the moments that actually matter. The agents do the rest.
Every project follows the same arc — research, business plan, architecture, execution — with named decision gates between stages. You approve. We continue.
Most AI tools generate documents. WeYala’s agents execute — they send the partnership emails, manage the multi-week correspondence, build the schema, deploy the service. Two specialized squads, one orchestrator, full coverage of the work.
Real-world correspondence. Long-running. Adaptive. The agents that draft partnership outreach, regulatory comms, and customer-success replies — send them (with your approval), monitor your inbox for responses, follow up after a week, and regroup when six counter-parties decline and two ask for a call.
Code-writing agents. Each owns a surface: frontend, backend, database, security, tests, infrastructure. They run in isolated worktrees, write code, run tests, open PRs, get reviewed by an adversarial counter-agent before merge.
Between gates, WeYala works silently. No notifications. No status pings. No "the agent is thinking" indicators. When the agents need a decision, you see one clean modal.
Your dashboard needs three staff seats per practice, but the original brief assumed a single user. Adding multi-tenancy now means a fresh RLS layer plus an auth-flow rebuild — or we ship single-user v1 first and add tenancy in v1.1. Approve the scope expansion, defer, or rethink the brief?
A "project" can mean very different things. The same six-stage lifecycle and the same approval gates apply — what changes is which specialty packs load and which tools the squads reach for. A sample of the shapes WeYala covers:
Specialty packs are domain bundles the build squad loads when a project's vertical or stack calls for them — regulatory rules, schema patterns, edge cases the foundation model wouldn’t know without help. New packs ship continuously; the set below is illustrative.
Not a demo. Not a hello-world. CircleStocker — an inventory-intelligence SaaS for small medical and dental offices — gets a full rebuild end-to-end by WeYala. It’s our first end-to-end run; the platform validates against it.
Twelve to sixteen weeks. Build Squad writes the new schema, migrates 316,000 canonical products, ingests FDA GUDID and openFDA data, ships the frontend. Operations Squad runs the manufacturer-partnership outreach campaign — drafting first-contact emails, surfacing them for approval, navigating negotiations, onboarding data feeds.
If WeYala can deliver CircleStocker v2 end-to-end — shipping product, real partnerships, customers using it — the platform works. If it can’t, we learn exactly which subsystem failed.
CircleStocker is project no. 01. Yours can be no. 02.
AI-cost economics shift week to week. We’re tuning a model that pairs a subscription floor with transparent LLM passthrough and hard caps — so your spend is bounded and our margin stays honest. Final tiers publish when the unit economics are settled, not before.
If you have an idea you’d ship through WeYala in the next 90 days, we’ll work with you on a founder-pricing arrangement — you get the platform at cost while it’s in development; we get a real project to validate against.
Reach out: founder@weyala.ai.