AI sales agent
Researches inbound leads from their website and public sources, enriches the CRM record, scores fit against your ideal customer profile and drafts a personal first email for a rep to approve. It can also propose meeting times.
Agentic AI with guardrails
AI Agent Development: Custom Agents That Get Real Work Done
Our AI agent development work produces agents that take a goal, choose the right tools, act across your systems and check their own results, with your team approving anything that matters. We start narrow, measure everything and widen the agent's job only once it has earned trust.
Wix Legend Partner · 2,000+ projects since 2014 · 1,400+ client reviews
What is AI agent development?
AI agent development is building software in which a language model works toward a goal over several steps: deciding what to do next, calling tools like your CRM, inbox or database, checking the results and asking a person when it should. It suits teams whose multi-step, judgment-heavy work is spread across several systems.
Custom AI agents we build
Each agent gets one clearly defined job, a short list of tools and a person who owns its results.
Customer support agent
Reads a ticket, checks the order or account, applies your policy (for example, refunds under a set amount) and drafts or sends the reply. Anything outside policy is escalated with a summary.
Operations agent
Matches invoices to purchase orders, chases missing paperwork, checks stock levels and compiles the Monday report from five different tools.
Internal knowledge agent
Answers staff questions from your wiki and SOPs, then handles the follow-up: opening the ticket, requesting access or scheduling the task.
Research and briefing agent
Gathers information from approved sources, compares options and writes a structured brief with citations for a person to review.
Website and store agents
Goes beyond answering questions on your Wix, Shopify or custom site: changing a booking, starting a return or building a quote. For question-answering only, an AI chatbot is simpler and cheaper.
Agentic AI development: how we build agents you can trust
Tight tool definitions
Each tool does one thing, validates its inputs and returns clear errors. The agent can only call tools on its list, with only the permissions that job needs.
MCP (Model Context Protocol)
MCP is an open standard for connecting AI models to tools and data, now governed by the Linux Foundation's Agentic AI Foundation. Building your connectors as MCP servers means they can be reused across models and AI apps instead of rebuilt for each one.
Memory with limits
Working memory covers the current task. Long-term memory, such as customer preferences or past decisions, is stored only where you approve, in your own database, with retention rules.
Human-in-the-loop approvals
For anything external or irreversible (sending emails, issuing refunds, editing records, moving money) the agent proposes and a person approves in Slack, email or a dashboard. Approval thresholds can loosen as the agent proves reliable.
Evaluation
We build scenario tests that score task success, correct tool use and policy compliance, then re-run them on every change and whenever a provider updates its model.
Monitoring and cost control
Every run is traced: what the agent saw, which tools it called and what came back. Alerts fire on failures, loops or unusual spend, and each run has step and budget limits.
Security
Credentials are least-privilege and read-only by default. Content from emails, web pages and uploaded files is treated as untrusted to defend against prompt injection. Secrets never sit in prompts, and every action lands in an audit log.
What AI agents still get wrong
Agents are useful, but the honest picture matters before you invest:
- Errors compound. Ten steps that are each 95% reliable succeed together only about 60% of the time. Fewer steps means fewer failures.
- Runs vary. The same input can take a different path, so we test many runs, not one.
- They cost more than workflows. An agent makes several model calls per task, which adds latency and usage fees.
- They can be manipulated. A malicious email or web page can try to hijack instructions, which is why permissions and approvals matter.
An agent makes sense when the next step genuinely depends on what the last one found. When the steps are always the same, AI automation is faster, cheaper and easier to debug.
Why choose Wix Engine as your AI agent development company
We connect to the systems agents depend on
Since 2014 we've delivered 2,000+ projects involving websites, stores, dashboards, APIs and webhooks. An agent is only as useful as its connections, and building connections is our core work.
Narrow first, then expand
Your first agent does one job, behind approvals. Autonomy grows only for actions that have proven reliable in measured results.
Model-agnostic
We build with OpenAI, Claude and Gemini models and choose frameworks per project, so you aren't locked into one vendor's roadmap.
Transparent by design
You can see every run's trace and cost. We hand over documentation and sign NDAs on request.
How an agent project runs
- 01
Free 30-minute call
We map the job, the systems involved and what could go wrong. Detailed proposal within 24 hours.
- 02
Workflow and risk mapping
Every action is listed and marked reversible or irreversible, approval points are agreed and success measures are defined.
- 03
Read-only prototype
The agent works on real data but can't change anything. We score it against test scenarios.
- 04
Supervised pilot
Actions are switched on behind approvals, and your team reviews each one the agent proposes.
- 05
Production and monitoring
Tracing, alerts and cost limits go live, and autonomy expands only where the pilot proved it safe.
- 06
Ongoing evaluation (optional)
A retainer to re-test after model updates, add tools and review failures.
Tools & technologies
models
- OpenAI
- Claude (Anthropic)
- Gemini
- open-weight models
agent frameworks
- OpenAI Agents SDK
- Claude Agent SDK
- LangGraph
- LangChain
- Google Agent Development Kit (ADK)
protocols & integration
- Model Context Protocol (MCP)
- REST APIs
- webhooks
data & memory
- PostgreSQL
- pgvector
- Pinecone
- Redis
triggers & orchestration
- n8n
- Make
- Zapier
- scheduled jobs
observability
- LangSmith
- Langfuse
- custom logging dashboards
languages
- Python
- TypeScript
- Node.js
Work
Agent work
Agents build on AI work we already ship on live client sites. We've built custom AI chatbots for Canada Medical Notes, US Medical Notes and Sharon Homes, written with Velo and custom elements on Wix. We've also built an automation that issues a fiscal e-receipt through the eParagony.pl API for every pricing-plan purchase on a client's Wix site and emails the link to the customer. An agent adds the next layer: a defined set of tools it can call, and an approval step before anything important goes out.
How much does AI agent development cost?
Agent projects are part of our custom AI work, which starts from $8,000.
What affects the price:
- Number of tools and systems each connection needs building, permissions and tests.
- Risk of the actions agents that send, pay or delete need approval flows and audit logs.
- Evaluation depth more scenarios for higher-stakes work.
- Security requirements access reviews, data handling rules and hosting constraints.
Agents also have running costs: model usage per run (higher than a chatbot, because each task takes several calls), hosting and monitoring tools. We estimate these in the proposal.
Most clients start with a fixed-price prototype and pilot, then move to production with an optional monthly retainer. Send us the job you want an agent to handle and you'll get an estimate within 48 hours.
FAQ
Frequently asked questions
What is the difference between an AI agent and a chatbot?
A chatbot mainly answers questions in a conversation. An AI agent works toward a goal by taking several actions, like looking up records, updating your CRM and drafting emails, and decides which step comes next based on what it finds. Many projects combine both: a chatbot on the front end and an agent handling tasks behind it.
How much does it cost to build an AI agent?
AI agents with Wix Engine fall under our custom AI work, starting from $8,000. Price depends on how many systems the agent connects to, how risky its actions are and how much testing that requires. Running costs, mainly model usage per task, come on top. We send a detailed estimate within 48 hours.
What is MCP (Model Context Protocol)?
MCP is an open standard for connecting AI models to tools and data sources, such as a CRM, database or file system. Anthropic released it in 2024 and donated it to the Linux Foundation's Agentic AI Foundation in December 2025. Building connectors on MCP means they work across multiple AI models and apps.
Is it safe to give an AI agent access to our systems?
It can be, with the right controls. We give agents least-privilege, read-only access by default, require human approval for irreversible actions, treat incoming content as untrusted to block prompt injection, set spending limits and log every action. Access expands only after a supervised pilot shows the agent is reliable.
Can an AI agent replace an employee?
Usually not, and we don't pitch it that way. Agents are good at the repetitive, multi-step parts of a role: research, data entry, first drafts and routine checks. That frees people for decisions, relationships and exceptions, which agents still handle poorly. The usual goal is hours back each week, not fewer people.
How do you test an AI agent before it goes live?
We build scenario tests from real cases and score each version on task success, correct tool use and policy compliance. The agent then runs read-only on live data, followed by a supervised pilot where a person approves every action. Tests re-run whenever we change the agent or a provider updates its model.
What is an AI sales agent?
An AI sales agent handles the research and admin around selling. It enriches new leads, scores them against your ideal customer profile, updates the CRM, drafts personalized outreach and suggests meeting times. We set it up so a rep reviews messages before they're sent, protecting your domain reputation and your brand.
Pick one job. We'll build an agent that does it reliably.
Book a free 30-minute call to walk through the work you want handled. You'll get an honest read on whether an agent fits, and a detailed proposal within 24 hours.
Sohaib Mehmood
Owner & CEO
Wix Legend Partner · 2,000+ projects since 2014 · 1,400+ client reviews