# Self-integrating AI agents for sales, support and lead generation Algomo discovers and connects with the systems already powering your website to answer support questions from live data, sell from real stock and qualify your B2B buyers. Live in minutes · works on any stack · no credit card required ## AI purpose-built for your business's toughest challenges ### Support agent Order status, availability and policies, answered from your live systems. [Customer support](/solutions/customer-support) ### Sales agent Checks real stock, quotes the real price, adds to the basket. [Sales](/solutions/sales) ### Lead gen agent Qualifies the prospect, routes the conversation, books the meeting. [Lead generation](/solutions/lead-generation) ## Live in minutes, better every week ### 01 Build Give Algomo your website. It finds the endpoints your pages already call and builds its own tools to use them. Try it yourself, against your live data, before a visitor ever does. ### 02 Optimize Use your agent to analyse your traffic, conversations and website activity, run experiments, and make changes, all conversationally. It learns from what your customers actually ask. ### 03 Scale Add another site, another language, another agent from the same workspace. Chat is unlimited, so growing traffic alone never raises the bill. ## The Algomo difference ### Connects itself to your stack **It finds the endpoints your own pages already call.** Point Algomo at your website and it reads what your pages read: the stock check, the order lookup, the booking search. Then it builds tools to use them and answers from live data. **No integration project.** One snippet, live in minutes, because the agent does its own integration work. Systems behind a login are connected with us. **Self-healing.** A watchdog watches every connection. When a redesign breaks an endpoint, it rebuilds the mapping on its own; you find out because it still works. [Self-integration](/product/self-integrating-agent) ### Run the whole platform by talking to it **A platform for humans and AI agents equally.** Whatever you can see and change in the app, your AI tools can see and change over MCP, Claude Code included. Describe the change and it lands; no dashboard to learn. **Everything it does can be questioned.** Ask what it changed, what it called and why, and it answers with the specifics. If it needs a tool it does not have, it builds one and shows you. **It knows your company, once.** What you teach it is shared knowledge: every channel, every agent you run, and the AI tools you point at it all work from the same understanding. [AI-first platform](/product/ai-first) ### A real assistant, not a chatbot **It works the page with the visitor.** Anything your site can already do is in reach: filter the list, apply the code, add to the basket, hold the booking. When doing is faster than explaining, it does. **It has followed the journey.** It knows the page the visitor is on and what they have seen and searched this visit. Nobody has to describe or repeat anything. **The page and the assistant share one session.** What the visitor does, it sees; what it does, they see: their own prices, their region, their bag. Add to the bag by hand and it knows. Ask it to add, and the bag updates. Any website, no platform app. [Co-navigation](/product/co-navigation) ## The hidden cost of AI agents is the humans behind them **Behind almost every “autonomous” agent is a forward-deployed engineer** doing two jobs: wiring the agent into your systems, and translating what the business wants into what the agent does. Postings for that role grew more than 800% in 2025, the deployments still take months, and Gartner predicts over 40% of agentic AI projects will be canceled by the end of 2027. It is a model only enterprises can afford. **We built the agent to do both jobs itself.** It discovers your endpoints and builds its own tools: that is self-integration. It turns plain-language requirements into behaviour: that is AI-first. It can, because it runs in your visitor's session, on the interface your site already exposes. That is the whole company. [Read our thesis](/resources/thesis) ## The complete platform for customer agents ### Widgets Answers with the real thing: product cards, carts and booking panels, not just text. ### Agent builder Describe what you want in plain language and it builds the rules, answers and workflows. ### Production platform Every change is staged in a session. Review the diff, preview it, then ship it. ### Multi-agent One agent can invoke another to finish a task, then carry on with the result. ### Tools Built from your own endpoints, plus any you add. ### Integrations Works with what your site already runs. ## Built for your industry ### Retail and ecommerce Whether a size is in stock, when the order will arrive, how returns work: these questions decide the sale, and the agent answers them from your store's live data. [Retail and ecommerce](/solutions/retail-ecommerce) ### Travel and hospitality Travel questions are always about a specific date, party and room. The agent answers them by checking the same booking system your own site uses. [Travel and hospitality](/solutions/travel-hospitality) ### SaaS Pricing depends on the plan, features on the tier. The agent answers from your own pages and systems, then qualifies whether the visitor is someone your team should talk to. [SaaS](/solutions/saas) ### Consulting Prospects read a few pages and still cannot tell whether you do their kind of work. The agent answers that directly and books the call. [Consulting](/solutions/consulting) ### Real estate Whether a listing is still available, what the service charge is, what fits a budget in an area: every one of those is a lookup, and the agent checks them on your own site. [Real estate](/solutions/real-estate) ## Questions, answered ### What does Algomo actually do? Algomo is an AI agent for your website that connects itself to the systems your site already runs. It answers support questions from live data, checks real stock and adds to the real basket, qualifies B2B leads and books meetings. It acts during the conversation and after it. ### What does "self-integrating" mean? Point it at your website. It finds the endpoints your own pages already call (the stock check, the order lookup, the booking search), builds tools to use them, and starts answering from the same live data your site shows. There is no integration project. ### How is Algomo different from Fin, Sierra or Decagon? Three ways. Algomo integrates itself: it starts from your website and builds its own tools, where others start from connectors, knowledge uploads or a deployment project. It acts on your site natively: it can work the page with the visitor, add to the real basket at the real price, hold the real booking. And you control it in plain language, from the chat, the app, or your own AI tools over MCP; you never file a ticket to change your own agent. ### What is it allowed to change, and who decides? Anything you allow, and nothing you do not. You describe the limits the same way you describe everything else, in plain language. If you forbid something, it does not do it, and it says why. ### Do I need developers to set it up? No. Setup is pointing Algomo at your site, and changes are sentences. If you do have developers, they get the same control over MCP and an API. ### What happens when my website changes? It notices, rescans and rebuilds its tools. You find out because it still works. ### How do I know it works before my customers see it? Talk to it yourself, against your live data, before a visitor ever does. Or open the live demos: agents built on real sites like Carhartt WIP and JD Sports, answering from those stores' own stock and prices. ### What does it cost? Pricing is per useful conversation, not per seat. You can start free, with no credit card. ## Take control of your AI customer experiences Live in minutes · works on any stack · no credit card required ## Every page - [The AI agent that does its own integration work](/product) — Algomo maps the APIs your site runs on, connects to them on its own, and takes instructions in plain language. The others send you engineers or a connector list. - [AI agents for every use case and industry](/solutions) — Every page here describes the same product pointed at a different job. Pick your use case, or start from your industry. - [Built for your industry](/industries) — Stock, availability, dates, prices, eligibility. The agent is for sites where visitors' questions can only be answered by checking a live system. - [One AI agent for sales, support and lead generation](/use-cases) — You set it up once. Each of these is the same agent, given a different job and different systems. - [Resources](/resources) — Articles, comparisons and the thinking behind the product. - [Pay when it works](/pricing) — Algomo is priced on outcomes. A useful conversation costs 20 cents, a conversion costs $10, and chat itself is unlimited on every plan. A conversation that goes nowhere costs nothing. ### Product - [From a URL to a working agent](/product/how-it-works) — Paste your URL and the agent wires itself into the endpoints your pages already call. No scoping call, no build phase. - [Manage everything in plain English](/product/ai-first) — Tell your agent what to change, and it happens. No dashboard to click through. - [Connects itself to your stack](/product/self-integrating-agent) — Algomo finds the endpoints your own pages already call, then integrates with them. No integration project. - [Not a chatbot, a real assistant](/product/co-navigation) — Algomo follows your visitor's actions and helps with full context: it knows which page they are on and what they have already seen. If a step is faster to do than to explain, the agent does it. - [Discovers and works with your existing stack, from day one](/product/integrations) — Most AI agents come with a fixed list of integrations. Algomo finds the endpoints behind your own pages, we help connect anything behind a login, and if a tool is missing it can write one. - [Customer-operations infrastructure for your AI agents](/product/developers) — Every tool, rule and action Algomo builds is exposed over MCP. The interface we use to build an agent is the one you get. - [MCP reference](/product/docs) — Roughly 60 operations across these groups. - [An AI agent for Shopify that sells from your live stock](/product/shopify) — Algomo reads the same endpoints your storefront already calls. It knows stock, variant and price, and can put the item in the customer's real basket. - [An AI agent for WooCommerce, without a plugin project](/product/woocommerce) — Algomo works from the same data your store runs on, so it does not expect a standard install. - [An AI agent for commercetools, without the integration project](/product/commercetools) — Algomo learns the endpoints behind your storefront, so a bespoke stack is the normal case, not an extra cost. - [An AI agent that quotes real D-EDGE rates](/product/d-edge) — Algomo checks the same booking engine that sits behind your site, so the rate it quotes is the rate the guest would be offered. ### Solutions - [An AI support agent that answers from your live systems](/solutions/customer-support) — Algomo connects to the systems behind your website, so it can answer the questions that actually cause tickets: order status, stock, sizing and order changes. - [An AI sales agent that sells from your live stock](/solutions/sales) — Algomo checks what is genuinely available, quotes the price that visitor would see, and can add it to their basket. Checkout stays yours, and so does the sale. - [An inbound AI SDR that qualifies visitors and books meetings](/solutions/lead-generation) — Most of your traffic will never fill in a form. Algomo works your website the way an SDR would: it greets the buyers worth greeting, answers first, qualifies in conversation, and books the meeting on the right rep's calendar, at any hour. - [Help more shoppers without adding extra agents](/solutions/retail-ecommerce) — AI agents for ecommerce handle order tracking, returns and more, instantly. Free up your team, reduce tickets, and support more shoppers without extra effort. - [Fill more rooms without growing the front desk](/solutions/travel-hospitality) — Algomo answers rate, availability and property questions instantly, from the same booking system your own site uses. Fewer calls for your team, more guests finishing the booking. - [Answer the buyers who will never fill in your form](/solutions/saas) — Algomo answers pricing, plan and integration questions from your own pages, qualifies the visitor by talking, and books the demo in the conversation. - [Turn readers of your work into booked calls](/solutions/consulting) — Prospects read a few pages and still cannot tell whether you do their kind of work. Algomo answers that directly, qualifies by talking, and books the call with the right person. - [Answer every listing question while the buyer is still looking](/solutions/real-estate) — Availability, service charges, what fits a budget in an area: every one is a lookup, and Algomo checks your live listings, books the viewing, and hands the enquiry over with the context attached. ### Resources - [The hidden cost of AI agents is the humans behind them](/resources/thesis) — Why every agentic AI deployment quietly ships engineers, why the deployments still fail, and why we built an agent that does the engineers' job itself. - [Lessons from building AI agents that do real work](/resources/blog) — What we learn along the way, including the dead ends. - [How we compare](/resources/comparisons) — Most vendors in this category send engineers to wire your systems up. Algomo's agent does that work itself. - [Why Algomo](/resources/why-algomo) — The hard part is connecting an agent to the systems that hold the answers. Most vendors hire engineers to do it per customer; we built the agent to do it itself. - [Algomo](/resources/about) — We build the agent that does its own integration work. - [Algomo vs Sierra](/resources/vs-sierra) — Both build agents that take real action. The difference: Sierra sends engineers, Algomo sends an agent that finds your APIs and connects itself. - [Algomo vs Intercom Fin](/resources/vs-intercom) — Fin is good at answering. The difference shows up the moment the visitor wants something done rather than explained. - [Algomo vs Decagon](/resources/vs-decagon) — Decagon assigns people to each deployment. Algomo automates the step those people perform. - [Algomo vs Gorgias](/resources/vs-gorgias) — Gorgias is a helpdesk with an agent attached. Algomo sells as well as supports, on any platform, because it works from the systems your site already calls. ### Case studies - [GoMonte](/case-studies/gomonte) — case study, Real estate. A property agency in Montenegro, where almost every enquiry is about one specific listing: whether it is still available, what it costs to hold and what fits a budget in an area. - [Airbnb](/case-studies/airbnb) — live demo, Travel and hospitality. A demo Algomo built against the public Airbnb site to show an agent answering from live availability rather than from a help centre. - [Programica](/case-studies/programica) — case study, SaaS. A Quebec software company selling management software, where a visitor has to work out which product and which tier covers what they need before anyone can help them. - [Gymshark](/case-studies/gymshark) — live demo, Retail and ecommerce. A demo Algomo built against the public Gymshark storefront to show an agent checking real stock and moving a visitor towards checkout. - [YouJump](/case-studies/youjump) — case study, Leisure venues. Indoor trampoline parks across France, where the question is always about one venue on one date: opening times, age limits, birthday bookings and whether there is space. - [Elite Garages](/case-studies/elite-garages) — case study, Car servicing. Independent tyre, MOT and servicing garages across the South and South East of England, where the answer depends on the vehicle, the branch and what the branch can fit in. - [Carhartt WIP](/case-studies/carhartt-wip) — live demo, Retail and ecommerce. A demo Algomo built against the public Carhartt WIP storefront, covering size and stock questions, delivery to a given country, and adding to the basket in the visitor's own session. - [Dukley Hotels](/case-studies/dukley-hotels) — case study, Travel and hospitality. Hotels and residences in Montenegro, where a question is only answerable against a date, a party size and a property, and where the price a guest is quoted has to be the live one. - [JD Sports](/case-studies/jd-sports) — live demo, Retail and ecommerce. A demo Algomo built against the public JD Sports storefront to show an agent working the same basket the shopper is using. ### For agents - [Set Algomo up over MCP](/agents.md) — install instructions for a coding agent. - Every page here answers in markdown: add `.md` to any URL, or send `Accept: text/markdown`.