MANAGED CUSTOM AI AGENTS

Custom AI agent development services, built and run for you.

We build a custom AI agent for the workflow you name, deploy it into your systems, and run it in production for you. One setup fee plus one monthly subscription. Model APIs, hosting, monitoring, and ongoing refinement are bundled in. No separate invoices for the cloud or for the model providers.

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WHAT YOU GET

An agent that runs your workflow, plus a team that runs the agent.

You get a working AI agent that runs the workflow your team does by hand today, deployed into the systems you already use. The part most teams underestimate is everything around it: the engineering that keeps its accuracy from drifting, the integrations that keep it honest about what is actually happening in your business, and a senior engineer on the other end of the line when something breaks. The setup builds it. The monthly subscription keeps it working, so you never have to staff a team to babysit it.

  1. A custom AI agent, built to your workflow

    An agent tuned to your specific workflow, your terminology, and the way your team actually decides things. We build it on whichever AI model fits the task and wire it into the systems your team already lives in (your ERP, CRM, helpdesk, email, document store, and customer portals). It goes live in production at the end of the build, doing real work, not handed over as a prototype for you to figure out.

  2. A managed service, not a hand-off

    Once the agent is in production we keep running it. The monthly subscription covers hosting and infrastructure, the model API costs, observability and monitoring, ongoing prompt and retrieval refinement, evaluation against your workflow over time, and senior-engineer support when accuracy or behavior moves. You do not staff an internal AI team to keep the agent working. We do.

  3. One setup fee, one monthly fee, one team

    No separate invoices for the cloud, the model providers, or the tooling. The setup fee is fixed at signing and reflects the scope the proposal describes. The monthly fee covers everything in the managed service. New work or scope expansion is agreed in advance against a signed change order, so you always know the cost of every increment before it ships.

HOW IT WORKS

Scoped from an Assessment, built in weeks, run as a managed service.

Most build engagements follow an AI ROI Assessment. The Assessment maps the workflows, measures the baseline, projects the ROI, and recommends a build scope. The build proposal carries that scope forward as a precise specification: setup fee, monthly fee, number of steps the agent performs, number of integrations, target savings, target ROI. You sign off on a specification, not a tier.

A few engagements skip the Assessment: warm referrals where scope and fit are already clear, returning clients moving from other engagements, and strategic accounts with documented justification. For those, the first call does the scoping the Assessment would otherwise do. We do not sell a build straight off this page.

TYPICAL STARTING POINT

Start with the AI ROI Assessment.

The Assessment is a focused 2 to 3 week engagement that produces a ranked opportunity map and an implementation roadmap. If you proceed with a Managed Custom AI Agents build within 30 days of Assessment delivery, 50% of the Assessment fee is credited toward the Agents setup fee. The Assessment sets the engagement variables; the sales conversation does not.

Read about the Assessment

50%

Assessment fee credit

Applied to the Agents setup fee. The Assessment is a fixed fee, scoped on the intro call.

PRICING

No tiers. Every agent is scoped to the complexity of your workflow.

Leanware does not group Agents engagements into named tiers. Each one is scoped against objective variables (steps, integrations, target savings, target ROI), and the fees follow that scope. The reference engagements below show the shape of typical builds. Yours will land where the workflow lands, not where a tier menu says it should.

The reference engagements below are framed as representative scope. They reflect the structure and shape of typical builds without implying specific past customers. Real published case studies will replace them as clients clear them for publication. The AI Grader for Crowns case study below is real.

  • REPRESENTATIVE SCOPE

    3PL multi-channel intake

    3PL and B2B distribution

    A regional 3PL handling 600 orders per day across email, customer portal, and EDI. The agent orchestrates intake across three carrier systems, the WMS, and a customer-facing tracker.

    Steps
    8 to 12 steps
    Payback
    Month 4
    Integrations
    3 carrier systems, WMS, customer tracker
  • REPRESENTATIVE SCOPE

    MGA submission processing

    Insurance MGAs

    A specialty wholesale broker handling 800 submissions per month across five carrier portals, EZLynx, and email. The agent triages submissions, extracts ACORD data, and routes to the right underwriter.

    Steps
    10 to 14 steps with branching
    Payback
    Month 4
    Integrations
    5 carrier portals, EZLynx, email
  • REPRESENTATIVE SCOPE

    Manufacturing RFQ-to-quote

    SMB job-shop manufacturing

    A second-generation contract manufacturer running JobBOSS and Mastercam. The agent processes inbound drawings, extracts BOMs, runs cost estimation, and produces ERP-ready quote drafts.

    Steps
    6 to 9 steps
    Payback
    Month 4
    Integrations
    JobBOSS ERP, Mastercam, email

WHAT A PROPOSAL CARRIES

The variables on every engagement.

Each proposal commits to a precise specification along these axes. You sign off on the spec, not a tier name.

Setup fee
One-time fee for the build, fixed at signing.
Monthly fee
Managed-service subscription covering APIs, hosting, refinement, monitoring, and support.
Number of steps
Discrete decisions or actions the agent performs in execution. Primary complexity proxy.
Number of integrations
Systems of record the agent reads from or writes to.
Target savings, month 4
Monthly savings figure committed to in the proposal, sourced from the Assessment baseline.
Target ROI
Ratio of measured savings to engagement cost at the contracted measurement point.
Verbal summary
A one-sentence description of what the agent does, in your team's workflow specifics.
Tech stack
Model provider, orchestration layer, vector store if used, observability, hosting, evaluation framework.

IS THIS YOU

Three shapes of the teams this is built for.

If one of these describes your week, the engagement is sized for you. If none of them does, the first call will tell us both.

  • You run four-plus systems of record

    ERP plus CRM plus a helpdesk plus a custom database, or AMS plus carrier portals plus EZLynx plus email, or JobBOSS plus Mastercam plus a customer portal. The integration work is the hard part. You do not want to staff the engineering. You have been pitched by IT vendors who overpromised on integrations and the workflow still does not run end-to-end. The build lives in that integration layer.

  • You built something in-house and watched it drift

    An internal AI project, or a contractor build, or a Lindy workflow that got most of the way and then stalled. The accuracy moved after 90 days. The contractor disappeared. The agent is a maintenance burden your team cannot carry. The managed-service model is built for the failure mode you have already lived through.

  • You outgrew Lindy, Gumloop, Zapier Agents, or a vertical SaaS

    The platform got you most of the way. The workflow you are trying to automate has the kind of multi-system depth, regulatory logic, or edge-case handling the platform cannot follow. You are ready to pay for an engineer who can take ownership of the problem instead of forcing the workflow to fit the tool. Graduates from self-serve and verticalized AI SaaS are the strongest pipeline into this line.

HOW THIS IS DIFFERENT

Not a self-serve platform. Not enterprise consulting. Not verticalized SaaS.

Four categories of AI agent development company cover most of the market for AI agent work in the SMB band. Each wins on a specific shape of workflow. The Managed Custom AI Agents line is built for the workflows none of them serves well: multi-system, bespoke criteria, non-standard systems of record, or compliance demands that rule out a SaaS terms-of-service.

Comparison Managed Custom AI Agents Self-serve platforms Enterprise consulting Verticalized AI SaaS Other AI agencies
Pricing model One setup fee plus one monthly fee. APIs and hosting bundled. Per-task or per-seat SaaS. Cloud and model costs separate at scale. Hourly or fixed-fee scoping. Build and run billed separately. Per-seat or per-resolution SaaS. Build fee plus separate cloud, API, and retainer invoices.
Who delivers Senior engineers. No offshore handoff. You do, against templates. Partner ladder. Associates do the work. You configure. Vendor support, no engineer relationship. Mixed. Often subcontracted.
Best fit Multi-system, bespoke logic, compliance-sensitive workflows. Simple, single-workflow agents. Fortune 500 scoping engagements at $200K and up. Simple, high-volume, low-uniqueness workflows in their vertical. Variable. Depends on the agency.
Build timeline 3 to 10 weeks from Assessment-led proposal. Days to weeks, you build it. 6-month discoveries before build. Onboarding in weeks. No custom build. Variable.
Ongoing support Bundled into the monthly fee. Senior engineer in the loop. Community or paid-tier support. Separately scoped run engagement. Vendor support against SaaS SLA. Often a separate retainer.
Where it loses Simple agents a self-serve platform could already handle. Multi-system integration, bespoke criteria, compliance constraints. SMB price points. Engagement size and timeline. Workflows the SaaS template cannot follow. Bundled pricing. Engineer-led discovery as a real product.

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.

SELECTED WORK

A published case, with more to come.

We are migrating our case studies from our previous site. The AI Grader for Crowns engagement is the one Managed Custom AI Agents case we have been authorized to publish so far, and it shows the managed-service model in practice (custom orchestration across multiple model providers, continuous refinement, evaluation against real data over time). More will follow as clients clear them for publication.

Multi-provider AI evaluation backend in production across OpenRouter, OpenAI, Google, and Anthropic

University of Colorado (Evan Menke)

A custom AI agent built with the University of Colorado that evaluates dental student crown preparations against configurable rubrics. Multi-model orchestration across OpenRouter, OpenAI, Google, and Anthropic, integrated with a Base44 frontend.

Managed Custom AI Agents Read case study
View all case studies

CLIENT VOICE

From the engineer running the first published agent.

I presented this to my clinic and the response was strong. Leanware did excellent work, and we're going to use feedback from real evaluations to keep refining the AI agent, improving grading accuracy organically as it sees more cases.

EM

Evan Menke

University of Colorado

See all client reviews

FREQUENTLY ASKED

Questions we hear on the build proposal.

Most of these come up after the Assessment, before the build engagement starts. The answers below match what actually happens.

  • 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 ROI 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.
  • 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 ROI 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, or Zapier Agents?
    Self-serve platforms win on simple, single-workflow agents under $15K. They lose on multi-system integration, on bespoke criteria the templates cannot encode, on regulated workflows that need audit logs, and on multi-agent orchestration. Graduates from self-serve tools are this line's strongest pipeline. The first call sorts whether a platform would actually serve you well; if it would, we say so.
  • How is this different from verticalized AI SaaS like Avoca, Compass, or Black Ore?
    Verticalized AI SaaS wins on simple, high-volume, low-uniqueness workflows inside its vertical at SaaS pricing. It loses on workflows the SaaS template cannot follow: non-standard systems of record, bespoke criteria, multi-system orchestration the vertical product does not cover, or compliance constraints that rule out a SaaS terms-of-service. Teams who have hit a workflow their vertical SaaS cannot follow are the second-strongest pipeline into this line.
  • 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.
TRACK RECORD
READY TO TALK

Talk to someone who gets your business. And can build the solution.

We work to understand the workflow you have in mind, check whether it clears our four-month payback bar, and propose either an Assessment or, where the scope is already clear, a build proposal directly. If it is not a fit for us, we say so directly.

Tell us about the workflow you have in mind. Someone who understands the business and the engineering will review it, check whether it clears our four-month payback bar, and propose either an Assessment or, where the scope is already clear, a build proposal directly. If it is not a fit for us, we say so directly.

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