Custom AI agents for your workflow, built and run for you.

Two things make this engagement different in kind. The team that scopes the build can also run it in production, so the proposal commits to numbers the team has to meet at month 4 against measured client savings. And the pricing is bundled: one setup fee, one monthly fee, no separate cloud or model-provider invoices. You sign one contract and pay one vendor for the agent and everything that keeps it running.

• How much does a custom AI agent cost? +

  It depends on the complexity of your workflow, so we do not publish a price. Every agent is priced as one setup fee plus one monthly subscription, and the monthly fee covers model API costs, hosting and infrastructure, ongoing prompt and retrieval refinement, monitoring, and standard support. What yours costs is set by the AI Readiness Assessment, which scopes the agent against your specific workflow, systems, and target savings, so the proposal carries a precise figure rather than a guess. The reference engagements on this page show the shape of typical builds.
• What workflows do you build custom AI agents for? +

  Priority workflows on this line are multi-channel intake (email plus chat plus portal plus voice as a unified intake layer), document extraction (insurance ACORDs, real estate leases, financial statements, manufacturing drawings, logistics BOLs), RFQ-to-quote for manufacturing and insurance MGAs, AP and invoice processing where multi-system reconciliation matters, lead qualification and SDR triage against custom criteria, customer and vendor onboarding (3PL EDI mapping and SOP intake is the anchor example), and compliance and audit prep in regulated verticals. The strongest fit is workflows that touch four or more systems of record or that carry compliance constraints a SaaS terms-of-service cannot meet. Simple, single-workflow agents are better served by self-serve platforms like Lindy, Gumloop, or Zapier Agents, and we will say so on the first call.
• Do you offer AI automation services, or only AI agents? +

  Both, because on this engagement they are the same thing. An AI agent is how we deliver business process automation when the workflow crosses several systems or needs judgment at each step. If your process is a simple trigger-and-action sequence, a platform like Zapier or Make will serve you better and cost less, and we will say so on the first call. Once the workflow has outgrown that, the agent is the automation, and the monthly fee covers keeping it running.
• How is this different from hiring an AI automation agency? +

  Most AI automation agencies configure platforms: they connect Airtable, HubSpot, Zapier, or Make and hand the workflow back to you to maintain. We engineer a custom agent with its own memory, integrations, and error handling, then operate it in production under one monthly fee. The trade-off is fit. A platform agency is the right choice under roughly $1,500 a month of total automation spend, or for single-system workflows. Above that, or when exceptions and multi-system context are the problem, an engineered agent is cheaper to own.
• We tried to build AI agents in-house and it stalled. Can you pick up where we left off? +

  Yes, and this is one of the most common entry paths into the line. Internal AI builds and contractor builds drift after 90 days because evaluation, prompt refinement, and monitoring are real engineering work that does not get staffed once the build ships. The managed service is built for that failure mode: senior engineers run the agent in production, refine prompts and retrieval as your data shifts, and meet you at month 4 to compare measured savings against the target. The Assessment surveys what was built, decides whether to extend it or replace it, and produces a scoped proposal accordingly. There is no requirement that we start from scratch.
• How long does the build take? +

  Three to ten weeks from the Assessment-led proposal, depending on the number of steps the agent performs, the number of integrations, and the complexity of the verification logic. The build runs in parallel with weekly check-ins. The agent lands in production at the end of the build engagement, not as a prototype to be handed off.
• What's included in the monthly fee, and what isn't? +

  The monthly fee covers model API costs (OpenAI, Anthropic, Google, Azure or whichever provider the build uses), hosting and cloud infrastructure, observability and monitoring, ongoing prompt and retrieval refinement, model evaluation against your workflow as your data shifts, and senior-engineer support when behavior or accuracy moves. There are no separate invoices for the cloud or for the model providers. What is not included: scope expansion or new workflows the agent did not originally cover. Those are agreed in advance against a signed change order so the cost of every increment is clear before it ships.
• Do you have to start with an Assessment? +

  Not strictly, but we recommend it for most engagements. The AI Readiness Assessment maps the workflow, measures the baseline, projects the ROI, and recommends a build scope, so the build proposal carries a precise specification rather than a sales-conversation estimate. If you proceed with a build within 30 days of Assessment delivery, 50% of the Assessment fee is credited toward the Agents setup fee. Some engagements skip the Assessment: warm referrals where scope and fit are already clear, returning Leanware clients moving from other engagements, and strategic accounts with documented justification.
• What if you don't recommend a build at the end of the Assessment? +

  That happens sometimes and it is the Assessment doing its job. If the finding is that a SaaS platform is the right answer, the deliverable says so. If the finding is that you should wait six months for platform-native AI to catch up, the deliverable says so. If the engagement does not clear our 4-month payback discipline (setup plus four months of subscription must be less than four months of measured client savings), the build proposal is not drafted at the recommended scope. We say so and refund unspent Assessment fees where appropriate.
• How do you handle multi-system integration? +

  Most engagements on this line are multi-system by nature: ERP plus CRM plus a helpdesk plus a custom portal, or AMS plus carrier portals plus EZLynx plus email. The integration work is the part most platform alternatives cannot follow, and it is the work that determines the setup fee. The Assessment maps the integration topology before the proposal lands, so the build commits to a number of integrations as part of the engagement variables and you sign off on that count up front.
• How is this different from Lindy, Gumloop, Zapier Agents, or a vertical AI SaaS like Avoca or Compass? +

  Self-serve platforms win on simple, single-workflow agents under $15K, and vertical AI SaaS wins on high-volume, low-uniqueness workflows inside its vertical at SaaS pricing. Both lose on the same things: multi-system integration, bespoke criteria the templates cannot encode, non-standard systems of record, regulated workflows that need audit logs, and orchestration the product does not cover. Graduates from both are this line's strongest pipeline. The first call sorts whether a platform would serve you well; if it would, we say so.
• Is Leanware an agentic AI development company? +

  Yes, in the plain sense of the term. The agents we build plan and act across several systems rather than answer questions in a chat window. Each one has tools it is allowed to call, memory and retrieval over your data, evaluation against your real cases, guardrails on what it may do without a person, and an escalation path when confidence is low. We do not use agentic as a tier or an upcharge. The engineering is the same for a three-step intake agent and a twelve-step submission pipeline; what changes is the scope and the fee. How to build an AI agent: the engineering behind it
• Do you build AI chatbots? +

  Only when a chatbot is the right shape for the workflow. Most of what we build acts rather than chats: it reads an email or a submission, checks it against your rules, updates the system of record, and hands exceptions to a person. If you need a support or intake assistant that answers from your documentation, we build that too, usually as the front end of a larger agent. AI chatbot development services on their own are well served by platforms, and we say so when that is the case.
• Do you offer custom AI development services beyond agents? +

  Yes, through the other lines. AI features inside a product you are building or rebuilding belong to Software Product Development. Putting AI into systems you already run, from a readiness assessment through integration, belongs to AI Integration and Consulting. This page covers the case where a whole workflow should run on its own as a managed agent. The discovery call routes you to the right one, and we say so when the answer is not this page. AI integration services and consulting
• What should I look for in an AI agent development company? +

  Four things separate an AI agent development company that ships a working system from one that leaves you with a demo. Ask who does the work (senior engineers or a delivery bench), whether they run the agent in production after launch or hand it off, how they price ongoing operation (one bundled monthly fee or per-hour maintenance), and whether they will tell you when an agent is the wrong answer. This service line is built around those four answers, and the comparison on this page shows how the rest of the market segments. See our 2026 ranking of the best AI agent development companies
• Who actually delivers the engagement? +

  Senior engineers, working remotely with your team. No partner ladder, no offshore handoff, no account manager layer between you and the person doing the build. The same engineer team that scopes the build also runs the agent in production, which is why the monthly fee can carry continuous refinement without becoming a maintenance contract with a different vendor.
• What size of company is this for? +

  US-based mid-market and SMB companies. Pre-revenue startups and solopreneurs are out of segment, and so are Fortune 500 companies running strict enterprise procurement processes. The people we usually work with here are a department head, COO, or CFO; C-level involvement is common for large multi-channel or regulated builds.