The platform

One workspace for your whole AI team

Kuvai is an AI agent platform where you build AI teammates that take on real work — grounded in your documents, connected to the tools you already use, and running on a schedule, with the governance to keep everything under your control.

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Inside the platform

The surfaces your teammates work across

Every teammate works in one workspace — shared projects, living documents, your connected tools, scheduled runs, and a memory that builds over time.

Projects

Shared context

Group files, chats and teammates around a piece of work, so everyone on your team is working from the same context.

  • Files, chats, artifacts and teammates in one shared context
  • Per-project chat and instructions
  • Workbench: extract insights, due diligence, presentations
FilesChatsTeammates

Living documents

Work that stays current

Documents and tables your teammates maintain — updated as the work changes, not left to go stale.

  • Self-updating documents and tables
  • Maintained by your teammates as the work changes
DocsTablesAuto-updated

Connected Systems

Connect virtually any tool you use

Connect virtually any tool your team already uses — your CRM, email, docs, calendar, project tools and more — securely, and only with your approval.

  • Connect virtually any tool your team uses — via OAuth, with your approval
  • A teammate only acts in the tools you connect, and only where you allow
GmailSalesforceSlack+ more

Uploaded files

Grounded in your knowledge

Upload your documents and your teammates work from them — your knowledge, not generic AI.

  • CSV, XLSX, PDF, DOCX, PPTX, text and image OCR
  • Vectorised for grounding (up to 150 MB per file)
PDFDocxSheetsSlides

Scheduled tasks

Runs on its own

Set work to run on a schedule, so the recurring jobs handle themselves without being asked every time.

  • Recurring or triggered runs
  • Pre-flight capability check before each run
HourlyDailyWeekly

Memory

It remembers you

Every teammate accumulates your preferences and context as it works — day 60 is more useful than day 1.

  • A per-teammate notebook
  • Accumulates your preferences and context over time
PreferencesContextPatterns

Built to compound

Teammates that get more useful the longer they work with you

Most AI starts cold every time. A Kuvai teammate builds operating context over time — so the more it works with you, the less you have to repeat yourself.

Memory

Each teammate keeps a private notebook of how your business works — your preferences, your systems, your standing rules, and summaries of past work. It doesn't reset between sessions, so you stop re-explaining the basics.

Curiosity

When you introduce a new project or connected system, a teammate can take a quick, read-only look, note the essentials, and use that context next time — getting oriented without a full tour. Bounded and opt-in.

Self-learning

After completed work, a teammate reviews how it went, captures durable facts, and proposes refinements to its own instructions — which you approve. It improves at your recurring work instead of repeating the same miss.

Autonomy

You choose how independently each teammate acts — read-only, draft-first, or trusted with in-lane work. Authority you grant deliberately, with every action logged.

Autonomy you control — four levels

Match a teammate's authority to the work and the trust it has earned. Most teams start at Propose.

  • ObserveWatch only — no auto-runs, no proposals. Maximum control for evaluation or sensitive work.
  • ProposeReads and explores on its own, but asks before any change. The default.
  • ActCreates new in-lane work on its own, but asks before changing anything you've already touched.
  • LeadBroad in-lane authority, including updating its own in-lane work — for high-trust, high-volume roles.

Sensitive actions — sending, posting, paying, publishing — stay gated at every level, and every action is logged with its reason.

Build a teammate

No code. No config screens. Just describe the job.

You build a Kuvai teammate the way you'd brief a new hire — in plain language. Kuvai suggests a role and the tools it needs, you ground it in your documents and connect your systems, and it starts working. The same flow, at two speeds: start from a ready-made role or build one from scratch.

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New teammate
Step 1 of 5

What should your team member do?

Keep my sales pipeline updated and follow up on every new lead within a day.
Recommended setup
SSales Coordinator
Connect tools
HubSpotGmailSlack
Ground its data
Sales playbook · contacts
Your new teammate starts working

What does it mean to build an AI teammate, and do I need to code?

Building an AI teammate on Kuvai means describing a job in plain language and getting a colleague built around it — grounded in your documents, connected to your tools, and running on a schedule. There is no code and no workflow to wire up.

This is the opposite of how most AI tools work. A no-code automation platform makes you draw a flowchart of triggers and actions; a chat tool makes you re-explain your business every session. Kuvai's build flow takes a sentence — "keep my pipeline reviewed and flag deals that have gone quiet" — and assembles a teammate with the right role, the right connected tools, and a place to ground it in your data. The catalog of ready-made roles and the from-scratch path are the same flow at two speeds: start from a suggested role, or describe something entirely your own.

The wedge: simpler than building automation (Zapier / Make / n8n), more capable than chatting with AI (ChatGPT / Copilot) — and built around your business, not someone's template.

What is an AI agent platform — and why does Kuvai build teammates instead?

An AI agent platform is software for standing up AI that takes real actions, not just answers questions. Most of them ship predefined agents for generic tasks, and you bend your process to fit the template. Kuvai is an AI agent platform in that sense — but built around the opposite idea: instead of adapting to a bot, you describe a job in plain language and get an AI teammate created around it, grounded in your own documents and connected to your tools. We call them teammates, not agents, because they own a job and adapt to how you actually work.

For a growing team, that distinction matters more than the label. A generic AI agent is quick to start but rigid, stateless, and unaware of your business; a Kuvai teammate handles the variation and exceptions a template can't, accumulates your context so it gets more useful over time, and drafts for your approval with every action logged. So if you're evaluating AI agents for your business, the real choice is a template you adapt to versus a teammate built around you — which is why our comparison of Kuvai vs predefined AI agents, and the AI agent definition in our glossary, both land on the same conclusion: for an SMB, a teammate is the better model.

Most AI agent platforms hand you a template to adapt to. Kuvai builds a teammate around your job — grounded, governed, and yours.

How do you build a teammate? The five-step flow.

No templates to wrestle, no code. Tell Kuvai what you need done, connect the tools it should use, point it at the data it should know — and your new teammate gets to work.

01

Describe the job

In your own words. Kuvai suggests a role and the tools it will need, or you start from scratch.

02

Identity & style

Name the teammate, give it a persona, and set the tone of voice it should write in.

03

Connect tools

Plug in the systems it should work in — your tools, connected securely and only with your approval.

04

Ground its data

Point it at the projects and documents it should rely on, so it works from your knowledge, not generic AI.

05

Add to your team

Confirm, and your new teammate starts working — running on a schedule and surfacing what matters.

Step 1 also recommends a matching ready-made role you can adopt with one click — the catalog and custom creation are the same flow at two speeds.

Why build a teammate instead of wiring up automation?

Building automation (Zapier / Make / n8n)

  • You design the logic: every trigger, every branch, every action, by hand.
  • It does exactly what you wired — and nothing it wasn't told to.
  • No judgement: it can't read a document and decide what's missing.
  • Breaks silently when an input changes shape.
  • You maintain the flow forever.

Building a Kuvai teammate

  • You describe the outcome; Kuvai assembles the teammate around it.
  • It owns the job end-to-end and handles the variation, not just the happy path.
  • It reads, checks against your documents, and exercises judgement.
  • It accumulates your context — more useful on day 60 than day 1.
  • It drafts; you decide. Every action logged with its reason.

Automation is for deterministic plumbing. A teammate is for the judgement work — reading, checking, drafting — that rules can't capture.

What does a built teammate do on day one?

Mortgage & Lending: an overnight document desk

A broker describes the job: "check every borrower package against our file requirements and chase what's missing." The built teammate processes 40 documents that arrived overnight, returns an 11-point completeness check per file, and queues a draft chase-email for each borrower.

Insurance: renewal comparison on a schedule

An agency builds a teammate to compare each renewal against the prior term and the client's coverage needs. It surfaces every changed limit, dropped endorsement and premium delta, and drafts a plain-English client summary.

Customer Support: grounded first-pass replies

A support lead describes a triage-and-draft job. The teammate is grounded in the product docs and policies, drafts answers accurate to the company's actual terms, and routes genuinely novel tickets to a human.

Professional services: docs that stay current

A PM builds a Knowledge Manager to keep the team's process docs in sync with how work actually ships, on a weekly schedule, instead of letting them rot between projects.

Finance: a monthly close that runs itself

A founder builds a Bookkeeper to categorise transactions, reconcile accounts and draft the monthly P&L from the month's documents — every figure queued for review before anything is filed.

Sales: a pipeline that stays current

A sales-led founder builds a Sales Coordinator to watch the pipeline, flag deals stalled too long, and draft the next follow-up — so nothing slips between calls and meetings.

Every teammate is grounded in your documents and stays in its lane — out-of-scope work is flagged, never guessed.

Security & governance

Built to be trusted with real work

The guardrails and transparency that let you hand a teammate real work — the controls that are actually in place.

They draft, you decide

Every sensitive action — sending, posting, publishing, writing to your systems — is drafted for your approval, never fired automatically.

Each teammate stays in its lane

A defined job with clear boundaries. Out-of-scope work is flagged and checks with you first — never guessed.

Everything is on the record

Every action is logged with its reason — a full audit trail you can review (90-day retention).

Your data is scoped to you

Files, projects and outputs are scoped to your account. A teammate only works with what you give it.

You approve every connection

Tools connect through explicit OAuth approval — a teammate only acts in the systems you've connected.

LLM-agnostic

Runs on OpenAI, Anthropic and Google Gemini via AWS Bedrock — not locked to a single model.

Building a teammate — common questions

Describe the job. Get a teammate built around it.

Start free today. Build your first teammate in minutes — no code, no credit card.

No credit card required · Free to start · Cancel anytime