Vibe coding gave developers teams of coding agents. Wrightery brings the same model to knowledge work. Your AI analysts research, cross-check, and draft from trusted sources; you review the evidence and make the final call.
Join the waitlist for early access to Wrightery.
The weekly investment memo, the compliance review, the diligence report — they repeat for years, produced largely by hand, every cycle, by expensive professionals. Each one is built from hundreds of documents, emails, tickets and records in every format, and the expensive part is deciding what they mean. Automation tools handled the clicks, not the judgment.
Documents, emails, tickets, meeting notes, database records — every format, and a different shape every cycle. There is no single stable schema for the whole job, so conventional integrations never captured it.
Reading, weighing sources, arguing both sides, deciding what actually matters. Rules engines and workflow builders break the moment a step requires an opinion.
Chat drafts a fragment, and you finish it by hand. Real expert work needs specialists who challenge each other, a review step, and someone accountable for the result.
Sources, judgment, exceptions and review standards are scattered across experts, documents and chat threads — never written down as something that can be run again.
Vibe coding gave developers an environment that understands the work: deep context, agents that act rather than answer, a durable artifact, and verification before anything ships. Wrightery points those same four things at the analyst.
Code has a compiler. A report does not. A test fails in seconds; an analysis can be fluent, plausible and wrong. That is why the evidence trail, the agents that challenge each other, and the approval gate are the product itself — not governance bolted around it.
Three steps, in plain language. No code, no node wiring, no waiting on engineering.
Say what you produce and how you judge it — the same way you'd brief a new analyst on their first day. Then point it at your documents, databases and sources.
It builds the workflow and staffs it — specialist agents with their own roles, sources and tools, plus the people who review and approve. Read it, change it, no engineer required.
The agents gather the evidence, cross-check each other and draft the deliverable — every claim traceable to where it came from. It stops at you before anything ships, and it runs again next cycle.
Not a mockup — the live workspace Wrightery uses today. Knowledge, agents, approvals, and the cost of every run, in one place.
Every workflow, agent and run in one place — with what it is costing you.
Everything the work needs — what your agents can read, what they can do, who reviews it, how it runs, and what comes out — composed into a single governed system instead of six tools you hold together yourself.
In a joint engagement with a U.S. consulting partner, the project team delivered a client-specific agentic solution for a managed IT services provider of roughly 4,000 people. A recurring report assembled from knowledge documents, support tickets, emails, meeting notes and database records went from hours to a few minutes.
Observed in that consulting project: validation of the problem and the approach, not a Wrightery product deployment. The U.S. consulting partner owns the customer relationship and the project IP; that provider is not a Wrightery customer. Wrightery was built independently from the reusable pattern the engagement revealed — and is in private build today, with no external customers yet.
A coding agent runs a test and fails in seconds. An analysis can be fluent, plausible and wrong — with your name on it. Six things stand in for the compiler this work never had.
A workflow earns more autonomy as it proves it can be trusted — you decide the pace, per workflow.
Every knowledge worker is an analyst some of the time — the recurring hours when you gather, check, weigh and write up. If you produce the same kind of deliverable on a cadence, that is the work Wrightery is built to run.
The deliverable does not change — your client still buys a decision they can act on, and you still put your name on it. What changes is the hours underneath. So the price follows the work, not the seat count.
When the client buys the deliverable, lower production cost lands as capacity and margin — not as a smaller invoice.
Underprice the work and still earn more than before. A competitor still paying for the full hours can't follow you down.
On an internal desk — risk, compliance, audit, FP&A — the same saving arrives as turnaround, coverage and a report produced to one standard every cycle.
Planned for individuals building their first analyst team.
The whole workbench, producing real deliverables on a cadence.
Governance, deployment, and scale on your terms.
Indicative for launch and subject to change. A light workflow consumes fewer credits than a deep research-and-review one, so pricing follows the work rather than a negotiated rate per report.
Wrightery is in private build. Join the waitlist and we'll bring you in as soon as a seat opens — then describe one deliverable you already produce, and watch a team of AI analysts research it, cross-check it and draft it, for you to review, decide and approve.
No credit card. We'll email you the moment your seat is ready.