AI built to handle the work nobody wants to do.

Four kinds of work, broadly. There's chat and phone: assistants that answer from your real pricing and hours, book the appointment, and hand off to a person when they should. There's automation, which covers the paperwork, the inbox, and the follow-up that currently depends on somebody remembering. There's insight: dashboards that tell you what changed this week, and forecasting built on your own history rather than an industry average. And there's content, from writing in your voice to an internal assistant trained on your own documents. All of it gets built around the systems you already run. We don't ask you to move to ours.

A single chatbot or automation starts at $3,000. Most clients land on our Professional tier at $7,000, which covers multiple agents and CRM and calendar integrations. Hosting is a monthly cost, and ongoing support and optimization run on a retainer billed at $150 an hour. Full-scale AI infrastructure for a larger organization starts at $25,000 and scales with scope. Those are real starting numbers, and you'll get a fixed price once we understand what you're actually trying to automate.

Yes. MCP, the Model Context Protocol, is the open standard AI assistants like ChatGPT and Claude use to connect to outside systems, and an MCP server is the connector on your side. We build public ones that let assistants answer questions about your business and book a call, and private ones that let your team's assistant work with your real systems. Every agent gets its own identity, reading is kept separate from acting, and messages to customers or anything involving money default to a dry run or a person's approval. upforge.io runs one you can try, and our plain-English guide at upforge.io/resources/mcp-servers explains how they work.

Our production systems run on OpenAI models today. Everything we build is model-agnostic, so the same architecture can route to Anthropic's Claude, Google's Gemini, or open-source models when a use case calls for it on cost, privacy, or speed. We pick the model per task rather than per project, so high-volume routine work runs on cheaper models while judgment-heavy work gets a frontier model. You'll always know which providers touch your data.

Yes, and it'll do a lot more than answer FAQs. It reads your knowledge base and documentation in real time, so it answers from your actual pricing and services instead of guessing. It connects to your CRM, so the conversation is personalized and the lead lands somewhere you'll actually see it. It books appointments, qualifies leads, takes orders and payments where that makes sense, and escalates to a human the moment a question needs one. It runs around the clock, in multiple languages. How much of your inbound it can take off your team depends on how repetitive that inbound is, and we'll give you an honest read on that before you commit.

It depends on what you're building. A single chatbot or content tool takes two to four weeks. A custom assistant wired into your backend takes four to eight. A full automation system spanning several workflows runs eight to sixteen weeks, and a large enterprise build can take three to six months. We work in short cycles with regular demos, so you'll see something running inside the first two weeks, and you can start using the early pieces while we build the rest.

We design every build around data security from the start. Your data is encrypted in transit and at rest, access is role-based, and every autonomous action is logged with an audit trail and approval gates. We don't train models on your proprietary data, and we scope AI access per project so one client's data never touches another's. For sensitive workflows we'll walk you through exactly where your data goes and which providers touch it before anything ships.

Traditional automation follows fixed rules ("if this, then that"). AI integration adds judgment on top: it reads context, makes decisions, handles exceptions, and improves over time. For example, traditional automation routes emails by keyword, while AI reads intent, sentiment, and urgency and routes them accordingly. We often combine both, with plain automation for predictable tasks and AI for the complex decisions that used to need a person.

Usually, yes, though we'd rather show you where than hand you a percentage. The savings come from a familiar set of places: support questions answered without pulling someone off other work, content that takes an hour instead of a day, data entry that stops happening, scheduling that stops leaking time, and equipment problems caught before they become downtime. Gartner projects that agentic AI will resolve 80% of common customer service issues and cut operational costs 30% by 2029, which tells you the direction of travel. What it's worth in your business depends on your volumes, so we start with a cost-benefit analysis on your actual numbers before you commit to anything.

Yes, and AI needs it. Models get retired, APIs change, and a prompt that worked beautifully in March can quietly drift by September. Maintenance runs on a retainer. A retainer is a deposit you pay up front. We bill against it at $150 an hour whenever we touch your project, for any reason, and send you a monthly report on what we did. That work covers performance monitoring, prompt tuning as models evolve, integration fixes when a vendor changes something underneath you, and retraining as your business data grows. You also get regular performance reviews and a quarterly session to look at what's worth automating next, now that the first thing is running.

That's most of what we do. You don't want a standalone AI tool sitting awkwardly beside everything else you run. We've connected AI to CRMs like Salesforce, HubSpot, and Zoho, to ERPs like SAP, NetSuite, and Dynamics, to Shopify, WooCommerce, and Magento, and to plenty of custom web apps, databases, and internal tools. Anything with an API is straightforward. When there's no API (and with older systems there often isn't), we build a connector or automate the interface directly. Tell us what you're running and we'll tell you honestly whether it's a two-week job or a real project.