Turn client AI requests into new project and ongoing service opportunities. You keep the account, infrastructure management, security, and managed-service relationship. PlatformBridge scopes and builds the custom business workflows that need engineering beyond your existing tools.
Your client. Your managed relationship. Our AI delivery team.
Discuss working togetherIn co-delivery, you lead the account. We do not replace your managed services or approach your customer for unrelated work. Before an introduction, we agree account boundaries, customer communication, and how follow-on opportunities are handled.
Agree our delivery price, then price your customer offer with your assessment, infrastructure, security, and advisory work included. See the potential margin before you sell, without hiring a permanent AI team first.
Scope the ongoing cloud, licensing, security, governance, and vCIO services your team will deliver. We can support the application and AI workflow through a separate managed engagement, with responsibilities and fees defined before launch.
Keep work your team can deliver profitably, and use existing products where they solve the problem. Bring us in when a client’s finance, sales, or operations workflow needs custom engineering you cannot readily staff. You gain a delivery team for that opportunity while your engineers stay focused on the services you already sell.
You know the customer and manage the environment. We bring founder-led application, AI, and integration engineering. The workflow runs in the customer’s infrastructure, with their data under their ownership.
Lead the account, customer contract in a co-delivery engagement, and the managed services in your scope: tenant configuration, networking, identity, access, infrastructure, and security. Work with the customer’s process owner to identify the opportunity and guide adoption.
Assess the workflow and economics, then build the application, AI steps, integrations, validation, and human review. Test with real examples, document the handover, and agree application maintenance and escalation alongside your support model.
Look beyond internal IT tasks to the document, email, and approval work inside finance, sales, and operations. These examples show how your managed services and our engineering fit together.
Manage the cloud environment, document access, identity, and security.
Build document intake, validation against finance records, and ERP handoffs, with exceptions routed to the customer’s finance team.
Manage approved email and CRM access, permissions, and the hosting environment.
Classify requests, retrieve customer context, and prepare responses or next steps, with review before consequential actions.
Set up secure document access, infrastructure, and data boundaries.
Extract information, check required fields and business rules, and send uncertain cases to an authorized reviewer.
Manage system access, integration credentials, and infrastructure monitoring.
Connect intake, validation, routing, and status updates across systems while preserving the customer’s approval authority.
Establish approved data sources, access controls, and retention requirements.
Gather supporting evidence, link findings to sources, and prepare review queues for the customer’s specialists.
Manage the CRM and cloud environment, permissions, and approved integrations.
Build enrichment, record validation, and follow-up workflows, with checks and approvals before updating customer records.
Use an account review or vCIO conversation to find one costly, repetitive workflow. Bring the process owner, the systems involved, and a sense of the volume and manual effort.
Use the 1–2 week AI Opportunity Sprint to assess the workflow, value, integrations, and delivery options. Agree how you package and price the assessment before proposing it to the customer.
Scope a Production Sprint or Embedded Deployment for the selected opportunity. We handle the application and AI engineering; you handle the environment and managed services in your scope.
You continue the infrastructure, security, and advisory services the customer needs. Optional Managed AI Operations covers our agreed workflow support, with a shared escalation plan and separately defined fees.
Each stage has its own scope and fee. An assessment does not commit either team or the customer to implementation or ongoing support.
See what the AI Opportunity Sprint includesStart with co-delivery: your customer offer includes our engineering and the services your team provides. White-label and referral arrangements can be discussed when they better fit the relationship.
Our starting model
You lead the account and customer contract. PlatformBridge joins as your named delivery partner.
Agree our delivery price, then set your customer proposal and margin alongside your own services. Define payment responsibilities and ongoing support before committing.
By arrangement
For an established partnership, discuss delivering under your brand with your team owning customer communication.
Agree wholesale delivery pricing, visibility, support, and responsibilities for the specific engagement before you offer it under your name.
For an introduction
If you prefer to introduce the opportunity, define the scope PlatformBridge will contract directly and the managed services that stay with you.
Agree any referral compensation, account boundaries, and future-work expectations before the introduction. This is a separate arrangement from co-delivery.
Clear answers on scope, responsibilities, and the value of bringing in a delivery partner.
Keep it when your team has the skills, capacity, and economics to deliver it well. Use us when hiring, ramp-up time, or a specialist build would block the opportunity. You can retain the customer engagement and your services while pricing our engineering into the work. Compare the total delivery cost and your retained margin before committing.
Use them. The assessment starts with the systems and capabilities already available. Custom work makes sense where a verified gap remains: connecting business systems, applying company-specific rules, handling exceptions, or putting a workflow into daily use.
We define an escalation path and support runbook before launch. Your team handles the infrastructure and managed services in its scope; application, workflow, model, and integration maintenance can sit with us under Managed AI Operations. Agree response expectations, fees, and who receives each type of issue before selling ongoing support.
In a 30-minute conversation with our founders, walk through the workflow, the services you want to keep, and the engineering gap. We’ll discuss how to assess and deliver it together, including customer ownership, pricing, and support, before a client introduction.
Scope an opportunity togetherOr email deploy@platformbridge.ai
