For SaaS, docs & support teams

An AI support agent trained on your docs.

Point it at your help center, docs, PDFs, and API. It answers from your own content — and cites its sources — deflects repetitive tickets, and can take real actions. Live in an afternoon. No enterprise demo required.

Agentize your SaaS in three steps.

Bring your APIs

Drop in an OpenAPI spec. Every endpoint becomes a tool your agent can call. Read-only mode keeps write operations safe until you're ready.

Add your knowledge

Upload docs, markdown, PDFs, or crawl a URL. We chunk, embed, and index — the agent retrieves the right context on every turn.

Ship a conversation

One API call starts a chat. Webhooks stream events as they happen. Multi-tenant scoped keys keep your customers' data isolated.

Everything a production agent needs.

OpenAPI → tools

Import a spec once. Every endpoint is a tool the agent can call. Toggle individual endpoints on or off per agent.

Knowledge bases

Markdown, HTML, PDF, text, or URL crawl. Auto-chunked, embedded, and semantically searched on every turn.

Model routing

Route simple queries to cheap models, complex ones to your best. Bring your own keys or use the shared pool.

Multi-tenant keys

Scoped API keys with agents, chat, knowledge, analytics, and admin scopes. Rotate with a 24-hour grace period.

Event webhooks

chat.*, tool.*, knowledge.*, capacity.* events. HMAC-signed payloads. Know exactly what your agent is doing.

Context strategies

full, auto, or aggressive compaction. Stay within token budgets on long conversations without losing the plot.

The difference

Not just answers — actions.

Most “doc chatbots” can only talk. Yours can do the thing the customer actually came for.

Answers, grounded

Every reply is pulled from your own docs and cites where it came from — so it doesn’t make things up.

Actions, not just talk

Drop in an OpenAPI spec and every endpoint becomes a tool. The agent can check an order or update an account — not just describe how.

Safe by default

Read-only mode keeps write operations off until you’re ready. Scoped keys keep every customer’s data isolated.

From spec to chat in one request

curl -X POST https://api.makeyouragent.ai/api/quickstart \  -H "Authorization: Bearer mya_live_<your-key>" \  -H "Content-Type: application/json" \  -d '{    "agentName": "Support Agent",    "systemPrompt": "You are a helpful support agent for Acme Corp.",    "openApiSpec": {      "source": "url",      "url": "https://api.acme.com/openapi.json"    },    "testMessage": "How do I reset my password?"  }'

One request. An agent with your APIs, your prompt, and a first successful chat.

or try it yourself →or install the Node SDK: @makeyouragent/sdk →
Architecture: your customer talks to your SaaS, which calls Make Your Agent, which uses your OpenAPI, your knowledge base, and routed LLMs.Your customerYour SaaS appMake Your Agentthe agent layerYour OpenAPI specYour knowledge baseLLMs (routed)

You keep your data.

You keep your models.

We handle the agent.

Production-ready from day one

Scoped API keys
Rate limits & quotas
HMAC-signed webhooks
Read-only mode
Audit events

Contact for pricing. Tiered plans coming soon.

Pricing

One integration. One monthly fee. No surprises.

We handle the build and keep it running. You keep full visibility into every cost.

€6,000one-time

Integration

We connect your product to a production-ready AI agent — your APIs, your knowledge base, your customers’ conversations. Scoped to your stack, deployed to your infrastructure.

Your tokens, your cost

AI usage

We bill you at cost — zero markup on every token. More tokens just means more customers served. Each month, you get a detailed consumption report so you know exactly where your usage goes.

€3,000/month

Maintenance

Unlimited requests — improvements, new intents, bugfixes, prompt tuning, whatever your chatbot needs. No ticket limits, no hourly billing, no waiting for a sprint cycle.

Book a call →30 minutes. No pitch deck.

FAQ

Support agents, answered.

How do I make an AI chatbot trained on my website or docs?

Create an agent, then import your content — markdown, PDFs, help docs, or a crawled URL. We chunk, embed, and index it so the agent retrieves the right context on every question. No code required.

How do I stop a custom GPT from hallucinating or making things up?

The agent answers from your imported content via retrieval, and surfaces the sources behind each answer. Grounding replies in your own docs — instead of the model’s open-ended memory — is what keeps it honest.

Can the chatbot cite its sources from my content?

Yes. Answers are drawn from your knowledge base, so the agent can point back to the documents it used.

Can I train a chatbot on my PDFs, Notion exports, and help docs?

Yes — markdown, HTML, plain text, PDFs, and crawled URLs are all supported as knowledge sources.

How long does it take to set up a no-code support chatbot?

You can have an agent answering from your docs the same day. Most teams are live in an afternoon, without an engineering project.

What is the difference between an AI agent and a chatbot?

A chatbot only answers. An agent can also act — call your API, check an order, or update a record — using the tools you give it, then report back in the conversation.

Can the AI agent take actions — like process a refund or update an account?

Yes. Import an OpenAPI spec and each endpoint becomes a tool the agent can call. Read-only mode keeps write actions off until you explicitly enable them.

How does the agent connect to my own API or tools?

Through your OpenAPI spec — every endpoint becomes a callable tool, with scoped keys and read-only safeguards so it stays safe in production.

How much can an AI chatbot reduce my support tickets?

It depends on how repetitive your inbound questions are, but a grounded agent that answers from your docs and takes routine actions deflects the bulk of repeat, self-serve tickets.

Is my data used to train someone else’s model?

No. Your content is used to answer your customers, not to train anyone else’s model.

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