Build a custom AI agent yourself
Drag the steps, connect them, replay against real data, then ship. It runs in your browser and you don't need an engineer.
Drag sideways to see the whole diagram
Drag a step from the library, drop it on the canvas, ship the run.
A custom AI agent is a workflow you design: which documents it reads, what rules it follows, which tools it calls, when it stops for a human.
Off-the-shelf chatbots don't know your policy book. Custom-coded agents take a quarter and a senior engineer. Certant gives you your knowledge and your rules on a visual canvas.
Five steps, start to production
What happens between wanting an agent and running one.
- Upload Point Certant at the documents or systems the agent needs to know. Certant reads them and builds the map.
- Pick a template Approval bot, Triage bot or Research bot. Start from one, change anything.
- Set the rules "Escalate anything over the limit you set." "Always cite the source." "Pause when it isn't sure." Written in plain English.
- Replay Run the agent over data you already have. See every step, and compare it against the previous version.
- Ship One click. Every version is kept and you can roll back. Our cloud, or inside your own walls.
Pick the closest template
Each one is fully editable. The shape is the same; what changes is what it decides.
Approval bot
Reads each incoming item (a contract, a leave request, a purchase), checks it against your policy, and either approves it, redrafts it, or hands it to a human with a citation.
- Best for legal, finance, HR
- Decision rules in plain English
- A person decides when it's unclear
Triage bot
Watches an inbox, ticket queue or webhook. Classifies the topic and urgency, routes to the right team, drafts a first response with a citation, and updates the system of record.
- Best for support, member services, IT
- Puts a first reply in the queue straight away
- Routes by topic, language and value
Research bot
Given a question, reads a set of documents you choose (your policy library, your case files, a specific archive) and returns a structured answer with citations. Same agent, different question every day.
- Best for analysts, advisors, knowledge work
- Returns a structured record or a written brief
- Always cites the source paragraph
What this costs against hiring
You can hire someone to build this, or you can build it yourself this week.
A senior hire and a quarter of ramp-up.
A senior AI engineer, a backend engineer, and a quarter of integration work. Then the same conversation next year when the policy changes.
One platform, and the person who owns the process owns the agent.
Build as many agents as you need. The non-engineer on your team owns them, and your engineers go back to the harder problems. See pricing .
What buyers ask
The questions teams ask before they start building.
Do I need to know how to code to build an AI agent?
No, most workflows are built visually: drag a node, connect it, configure it. You can drop in code for the cases that need it: custom logic, or calling an internal system nothing else reaches.
How long does it take to build a custom AI agent?
Most teams have a first useful agent working in one sitting. A production rollout with integrations and approvals takes a few weeks.
What templates are available?
Approval bot (review and approve incoming items against your policy), Triage bot (classify and route incoming work), Research bot (read a document set you choose and produce a structured answer). Each one is fully editable.
How much does it cost vs hiring a developer?
Cheaper than a senior AI engineer, and you don't wait for a hire. Pricing is credit-based and published on the pricing page .
Can I drop in code if I need to?
Yes. Any node can be a Python or JavaScript snippet. You keep the canvas, and you can still drop to code when you need to.
Can I try it without installing anything?
Yes. Sign up free, upload a document set, and build the first agent in the browser. Nothing to install.
Stop waiting on IT. Build the agent.
Free to try, nothing to install, and it runs in your browser.
If your team can draw the process on a whiteboard, they can build the agent. The whiteboard is the spec.