AI automation and integration, built into the stack you already run
AI automation services and AI integration services from an engineering team, not a prompt shop: workflows that remove the repetitive half of a job, and LLM and API integrations wired into the Craft CMS, Laravel, Shopify, CRM and ERP systems you already pay for. Built by the team that ships AI agents and RAG in production.
What we automate
Support triage
Incoming tickets and emails classified, enriched with the customer’s history from your CRM, routed to the right person with a drafted reply — the human sends it. The same grounding and handoff rules as our on-site AI agents, applied inside your helpdesk.
Invoice and document processing
Invoices, contracts, CVs, forms and PDFs read into structured fields, validated against your rules and pushed into your accounting system or ERP. AI process automation where the input is messy and the output has to be exact — so every extraction is checked, logged and reversible.
AI lead qualification and enrichment
Form submissions and inbound emails scored against your ideal-customer criteria, enriched from public sources and your own data, and written into HubSpot, GoHighLevel or your CRM with a one-paragraph brief for sales. Hot leads get a human in minutes; the rest get a polite, accurate reply.
Email automation
Inbound mail triaged, replied to from your approved content, and turned into tasks, tickets or CRM updates; outbound sequences personalised from real account data instead of merge fields. Every automated reply is labelled as such, and anything with a price, a promise or a complaint in it waits for a human.
Content operations
Drafts, translations, summaries, alt text, metadata and product descriptions generated inside Craft CMS or Shopify — as drafts for an editor, never auto-published. Structured content in, structured content out, with your tone of voice and your approval step kept.
Internal reporting
The weekly numbers assembled from your database, analytics and spreadsheets, explained in plain language and delivered to Slack or email — with the query behind every figure, so nobody has to trust a sentence they cannot check.
Back-office workflows
Onboarding checklists, approvals, reconciliations, order exceptions: the multi-step chores that currently live in someone’s head. AI workflow automation handles the judgement calls it can defend and escalates the ones it cannot.
Voice agents and call handling
Inbound calls answered, qualified and booked by a voice agent on Vapi or Retell, with transcripts and outcomes written back to your CRM and a warm transfer to a person the moment it matters. The conversational design lives with our AI agents service; the wiring into your systems lives here.
AI agents: assistants and voice agents →What we integrate
AI integration solutions that fit the stack, not the other way round. We add models and agents to systems you already run — no rebuild, no rip-and-replace.
Your platforms
- Craft CMS
- Laravel
- Shopify
- HubSpot & CRMs
- ERPs
- Internal tools
- Next.js front-ends
Models and APIs
- OpenAI API integration
- Claude API integration
- Gemini API
- Open-weight models
- Embeddings & vector search
Agent integration
- MCP server development
- Tool-calling agents
- RAG over your content
- WebMCP on your site
- Webhooks & queues
The unglamorous parts
- Human-in-the-loop review
- Evaluation suites
- Cost & rate-limit controls
- Audit logs
- Data boundaries
- Fallbacks & rollback
Tools and platforms we work with
One line each, honestly. We are an automation agency that writes code, so we pick the no-code tool when it is the right answer and skip it when it is not.
- n8n
- Our default for n8n automation when a client wants self-hosted, inspectable workflows; we work as the n8n developer or n8n consultant who also owns the custom nodes.
- Make
- Fast for marketing-side workflow automation with many SaaS endpoints; we keep the scenarios small and move anything stateful into code.
- Zapier
- The quickest glue there is. We act as the Zapier expert who tells you when a zap is enough and when you have outgrown it.
- Power Automate
- For Microsoft 365 shops: Power Automate AI flows for approvals and documents inside Teams and SharePoint, with the heavy lifting in a custom connector.
- Airtable & GoHighLevel
- Airtable automation for ops teams and GoHighLevel automation for agencies and local businesses — wired to real models instead of canned AI steps.
- OpenAI API
- GPT models for extraction, classification, drafting and tool calling, with structured outputs and cost controls.
- Claude API
- Long-context reading, careful tool use and agentic workflows; our own /ai agent and the Delight.ai Page Builder run on it.
- LangChain / LangGraph
- Stateful, multi-step agentic automation with checkpoints and human approval steps where a single prompt is not enough.
- CrewAI
- Role-based multi-agent crews for research and content pipelines, used sparingly and always behind an evaluation suite.
- LlamaIndex
- Document loading, chunking and retrieval over your PDFs, wikis and tickets when RAG is the job.
- MCP
- Model Context Protocol servers that expose your CMS, CRM or internal tools to Claude, ChatGPT, Cursor and other clients with proper OAuth and tool annotations.
- Vector databases
- pgvector on Postgres or Supabase by default, Pinecone when managed scale matters; embeddings and hybrid search tuned on your real queries.
- Voice platforms
- Vapi and Retell for inbound and outbound voice agents, integrated with telephony, calendars and your CRM.
Why Wideweb for AI automation and integration
Every claim below is already on this site, with the evidence behind it.
We ship AI agents and RAG in production
The agent on our /ai page is a production build — intent matching, retrieval over our own content, structured responses rendered as real UI, a brief-collecting flow that hands off to a human. Our Tech & AI Lead builds the same for clients today. The automation work on this page uses the same grounding, evaluation and handoff rules.
See the AI agents service →Integration is our home turf
Custom PHP and Craft CMS modules, integrations with HubSpot, ERPs, HR platforms and payment providers, headless front-ends on Next.js: an LLM is one more system to wire in correctly, with the same discipline about data flows, queues and failure modes.
Back-End development & integrations →Craft CMS Verified Partner
Verification by the Craft CMS makers included a direct review of our code and interviews with our clients. When AI content operations live inside Craft CMS, they are built the Craft CMS way — as modules and plugins your editors and your next developer can understand.
Craft CMS development →Small, senior, accountable
The person you talk to is the person who writes your code. Upwork Top Rated Plus with 154 completed jobs and a 100% Job Success Score; 83% of clients place repeat orders. We tell you when a feature is not worth building — and the assessment will say so in writing.
Honest about the hype
Gartner expects over 40% of agentic AI projects to be cancelled by 2027 for unclear value, cost or weak risk controls. Our answer is structural: a scoped pilot with a metric agreed first, an evaluation suite, a kill switch, and a report that is allowed to say “not yet”.
Found by AI, not just powered by it
Automation inside the stack is half the picture; the other half is whether AI search engines and agents can find and use your site. Our SEO & AEO work covers structured data, AI search visibility and agent readiness, so the two halves are built by one team.
SEO & AEO →How it works: Assess, Pilot, Production, Support
Assess
Start with the free AI readiness assessment: we rank your candidate use cases by ROI and feasibility, check the data and integrations each one depends on, flag EU AI Act duties, and name the use cases not worth building. The report includes a fixed quote for a first pilot — no obligation to take it.
Get the free AI readiness assessment →Pilot
One workflow, one integration, a fixed scope and a success metric agreed before we write code. We build it against your real systems and real data, with a human review step and an evaluation suite of real inputs, and we run it next to the current process until the numbers say it is better.
Production
The pilot hardened for the long run: monitoring, cost controls, rate limits, audit logs, rollback, and the data boundary documented explicitly. Your team gets the intent map, the prompts, the evaluation suite and the levers — no black box.
Support
Models change, APIs change, your content changes. We re-run the evaluation suite after every change, keep an unanswered-cases log, and tune the workflow on what actually arrives — or hand the whole thing to your own developers with documentation they can work from.
AI automation and integration we have shipped
Two production systems, both inside stacks the clients already ran. The full case studies cover the rest of each engagement.
An AI agent and MCP server inside Craft CMS
For Delight.ai we built Page Builder: a tool-calling agent that drafts and edits pages from inside the CMS, with a model picker across Claude, OpenAI and Gemini, and every edit landing in a draft, never on the live page. A 61-tool MCP server with its own OAuth 2.1 lets Claude Code, Claude Desktop and Cursor edit the same pages. Edits from Claude became visible in about 2.5 seconds instead of 17–20.
Delight.ai case studyContent pipeline, RAG and workflow integrations
The same plugin runs a multi-step article pipeline — keywords, research, brief, write, fact-check, SEO, meta, crosslinks — over a pgvector store fed by a sitemap crawler and document ingest, plus LLM translation into Korean and Japanese with translation memory. Comments become AI-drafted Jira tickets; mentions go out by email and Slack.
Delight.ai case studyAI commerce on a live WooCommerce store
For Stratus Infosystems, a Cisco Meraki reseller, we shipped a rule-based cart recommendation engine for required-license and attach logic and an inventory-aware product assistant on product pages — wired into the catalog, Zoho CRM sync and analytics stack we also run. AI-crawler readiness went up from a 3/100 baseline.
Stratus Infosystems case studyIntegration work we can show
From a marketing website built from scratch to an AI agent and MCP server living inside the CMS
View case study
From a storefront redesign to technical ownership of a live B2B hardware e-commerce platform
View case study
Architecting a seamless real-time data bridge between multiple ecosystems
View case study
Zero-loss lead generation for a multi-regional travel brand
View case studyHonest answers
What is the difference between AI automation and AI integration?
AI automation is the outcome: a workflow — support triage, document processing, lead qualification, reporting — that runs with less human effort because a model handles the judgement calls it can defend. AI integration is the engineering that makes it possible: connecting LLM and agent APIs to the systems where your data and your work already live — Craft CMS, Laravel, Shopify, your CRM and ERP. You rarely get the first without doing the second properly, which is why we sell them together.
How much does AI integration cost, and how long does it take?
Honestly: it depends on the use case and on how ready your data and systems are, which is exactly what the free AI readiness assessment measures — it ends with a fixed quote for a first pilot, so you see a number before you commit to anything. The difference between a pilot measured in weeks and an integration project measured in months is usually decided by whether your core systems have usable APIs and whether the data exists in one place. We will not quote a figure on a web page that we would have to walk back on a call.
Can you integrate AI into our existing CMS or CRM without a rebuild?
Yes — that is the point of this service. We add models and agents to the stack you run: a Craft CMS module, a Laravel service, a Shopify app, a HubSpot workflow, an MCP server in front of your internal tools. Structured content and clean APIs make it easier (Craft CMS is ideal), but integration problems are our home turf, and the assessment tells you up front which parts of your stack need preparation first.
How do you handle data privacy and EU AI Act obligations?
You decide what the model can see and what leaves your infrastructure; we design the data boundary explicitly and document it. Major providers do not train on API traffic by default, and we verify that per contract rather than assume it. For EU users, we build in the Article 50 transparency duties in force since August 2026 — AI that talks to people says so, AI-generated content is marked — and the assessment flags the Article 4 literacy duty and any high-risk use cases for your lawyer. We are engineers, not attorneys, and we say so.
Zapier alternative: when does custom integration beat no-code?
Zapier automation is the right answer while the workflow is linear, low-volume and tolerant of a failed run. It stops being the answer when you need branching logic with state, retries and idempotency, per-step cost control for AI calls, data that must not leave your infrastructure, or a bill that grows with every task. At that point a small custom service — or a self-hosted n8n with custom nodes — is cheaper to run and far easier to test. We will tell you which side of that line you are on; often the honest answer is “keep the zap”.
n8n or custom code?
n8n when the workflow is mostly glue between SaaS tools, your team wants to see and edit it, and self-hosting matters. Custom code when the logic is the product: complex validation, long-running agentic automation, strict audit trails, or anything that has to survive an API change at 3 a.m. Most of our n8n automation work ends up hybrid — n8n orchestrates, custom nodes and services do the parts that need tests. Either way you get the repository, not a dependency on us.
Power Automate vs custom AI automation?
If your company lives in Microsoft 365, Power Automate AI flows cover approvals, document routing and Teams notifications with the least friction, and we build inside it. Custom AI automation wins when the model needs your own data, when outputs must be validated and logged beyond what AI Builder offers, or when the workflow spans systems Microsoft does not own. The usual pattern: Power Automate as the trigger and the human step, a custom connector for the model and the validation.
Do we need an AI readiness assessment first?
Not strictly, but it is free and it is how our own process starts: it ranks your use cases by ROI and feasibility, checks the data and integrations each depends on, and produces the fixed pilot quote. If you already know the workflow, the metric and the systems involved, send that in the form and we skip to scoping the pilot.
Which workflow would you automate first?
Describe the process and the systems it touches — we will tell you honestly whether AI belongs there, and what it takes to wire it in.
Get in touchNot sure where to start? Begin with the free AI readiness assessment.
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