Fleet Capability • Custom AI Development

Custom AI Development
For MSP Partners and Their Clients

When standard prototyping is not enough, Petronella Technology Group builds custom AI solutions on our private fleet: multi-model orchestration, domain-specific RAG pipelines, compliance-grade inference, and custom fine-tuning. Your MSP owns the client relationship. We deliver the engineering.

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When Standard Prototyping Is Not Enough

The Petronella Fleet prototyping ladder handles the majority of MSP engagements. A PoC Lite at $35,000 proves feasibility. An MSP Fleet Prototype starting at $50,000 delivers a working system with a bill-of-materials and handoff documentation. Most regulated-SMB deals fit cleanly into one of those tiers.

But some client requirements push beyond standard prototyping into genuine custom AI development work:

  • Multi-model orchestration. The client's workflow requires multiple specialized models coordinated through an agent framework, not a single inference endpoint. A legal review pipeline might route documents through a classification model, an extraction model, a summarization model, and a compliance-check model in sequence, with branching logic at each stage.
  • Custom fine-tuning. Off-the-shelf models produce adequate but not excellent results on the client's domain-specific data. Fine-tuning on proprietary datasets creates a model that understands the client's terminology, document formats, and decision patterns in ways that prompt engineering alone cannot achieve.
  • Domain-specific RAG at scale. The client has hundreds of thousands of documents, regulations, or records that need to be searchable through natural-language queries with citation-grade accuracy. The vector database design, chunking strategy, retrieval pipeline, and re-ranking logic all require custom engineering beyond what a standard prototype delivers.
  • Compliance-grade inference pipelines. The client operates in a regulated environment where every inference must be logged, auditable, and reproducible. ITAR-compliant document processing, HIPAA-grade medical record analysis, or CMMC-scoped defense manufacturing workflows all require purpose-built pipelines with compliance controls baked into the architecture, not bolted on afterward.

For these engagements, Petronella Technology Group delivers custom AI development as an extension of the Fleet services-only model. We build on our private fleet, document the architecture, train your MSP team on operations, and hand off a working system. Your client procures their own hardware using the bill-of-materials we deliver. Your MSP manages the deployed system for the client under your own contract.

What Custom AI Development Means at Petronella

This is not application development in the traditional sense. Petronella's custom AI work focuses on infrastructure and model-layer engineering:

Private LLM Deployment

Self-hosted language models running on dedicated hardware with no data leaving the client's control perimeter. Model selection, quantization, serving infrastructure, and performance tuning for the client's specific latency and throughput requirements.

RAG Pipeline Engineering

End-to-end retrieval-augmented generation systems. Document ingestion, chunking strategy, embedding model selection, vector database architecture, retrieval pipeline, re-ranking, and citation generation. Built for the client's document corpus and query patterns.

Agent and Orchestration Builds

Multi-step AI workflows that coordinate models, tools, and data sources. Agent frameworks that route tasks, handle errors, maintain state, and produce auditable output suitable for regulated environments.

The distinction matters for MSPs: Petronella does not build web applications, mobile apps, or SaaS products. We build the AI infrastructure layer that applications connect to. If your client also needs a user interface, dashboard, or integration layer, that work is scoped separately and may involve your own development team or a third party.

Examples of Custom Work

These are representative engagement types, described generically to protect client confidentiality. They illustrate the scope and complexity of custom AI development work:

Private LLM for Legal Document Review

A regulated firm needs to review thousands of contracts, extract specific clauses, flag non-standard terms, and produce summaries for attorneys. The model must run entirely on-premises with no cloud connectivity. The pipeline ingests documents in multiple formats, normalizes them, runs extraction through a fine-tuned model, and outputs structured data with page-level citations. The MSP manages the deployed hardware and the inference endpoint; Petronella builds the pipeline and trains the MSP team on operations.

Medical Image Analysis Pipeline

A healthcare organization needs to process diagnostic imaging data through a classification model that flags anomalies for radiologist review. The pipeline must comply with HIPAA technical safeguards, log every inference for audit purposes, and integrate with the facility's existing PACS system. The architecture includes data ingestion controls, model serving with role-based access, audit logging, and an output interface that feeds results back into the clinical workflow.

ITAR-Compliant Document Processing

A defense manufacturing client needs to process technical documents that contain controlled unclassified information under ITAR restrictions. No data can transit cloud services, all processing must occur on authorized hardware, and the system must produce audit trails that satisfy DFARS 7012 preservation requirements. The pipeline includes document classification, entity extraction, redaction automation, and secure storage with chain-of-custody logging.

These examples describe categories of work Petronella Technology Group has the capability to deliver. They are not presented as specific past engagements or client case studies. Every custom AI development engagement is scoped individually based on the client's requirements, data, and compliance environment.

The Handoff Model

Custom AI development follows the same services-only philosophy as the rest of the Petronella Fleet program. Petronella does not sell hardware, does not rent multi-tenant infrastructure, and does not create ongoing dependencies that bypass the MSP.

The handoff sequence works like this:

  1. Petronella builds. All development and prototyping happens on Petronella's private fleet. Your client's data is processed under NDA with appropriate security controls for the data classification level.
  2. Petronella documents. Every engagement produces an architecture document, runbook, bill-of-materials for production hardware, deployment guide, and operations manual. Documentation is written for the MSP's technical team, not for Petronella's internal use.
  3. Petronella trains. Your MSP team receives hands-on training on the deployed system: how to monitor, how to troubleshoot, how to update models, and how to respond to performance degradation. Training is scoped in the statement of work and delivered before the handoff is considered complete.
  4. MSP manages. After handoff, your MSP operates the system for the client under your own managed-services agreement. The client writes checks to you. Petronella's direct involvement ends unless the MSP opts for ongoing Managed Service support.

This model matters because it preserves the MSP's economic position. You are not renting Petronella's infrastructure indefinitely. You are paying for engineering work that results in a system your MSP owns the operational relationship for.

Why Services-Only Matters for Custom AI

Hardware procurement is the MSP's responsibility in every Fleet engagement, and custom AI development is no exception. Petronella Technology Group does not sell GPUs, servers, or networking equipment. We do not take hardware margins, carry inventory, or assume warranty exposure.

For custom AI work specifically, this means:

  • The bill-of-materials is vendor-neutral. Your MSP can procure from NVIDIA, Supermicro, Dell, CDW, or any other source.
  • There is no lock-in to Petronella's infrastructure after the prototype phase. The system runs on hardware the client owns.
  • Petronella's pricing reflects engineering time, not hardware markup. This keeps the services margin clean for both Petronella and the MSP.
  • If the MSP wants help managing the procurement process, the optional $2,500 procurement coordination fee covers vendor selection, specs, purchase orders, and delivery tracking.

Fleet Tiers That Map to Custom Work

Custom AI development engagements enter the Fleet ladder at the higher tiers where scope and compliance requirements justify the engineering investment:

  • Compliance-Aware MSP Prototype at $75,000 is the entry point for most custom AI work. The 4-to-6-week timeline covers a working prototype with CMMC, HIPAA, or NIST 800-171 compliance mapping built into the architecture from day one.
  • Production-Ready MSP Prototype from $125,000 is for engagements that require a signed migration guarantee, 90-day post-handoff support, and an embedded CMMC-RP on the MSP's Slack channel during transition. This tier is inquiry-only and invoiced via wire or ACH after custom scoping.

Both tiers gate through a free 30-minute Discovery Call. No Stripe Payment Link is sent before the call because custom work scope varies too widely for self-serve pricing to be appropriate.

For MSPs Wanting an Ongoing Custom Development Relationship

If your MSP has multiple clients with custom AI needs, or a single large client with a multi-phase AI roadmap, the Petronella Strategic Partnership may be a better fit than individual Fleet engagements. The Strategic Partnership provides ongoing access to Petronella's engineering capability under a retainer structure rather than per-project pricing.

The Strategic Partnership is application-only and designed for MSP owners with $8M or more in annual revenue and a demonstrated pipeline of regulated-SMB clients who need private AI infrastructure. It includes full access to the Petronella capability stack, including custom AI development, CMMC Registered Practitioner bench, and DFE forensics, delivered by the team under a single retainer.

Non-Refundable and No-Guarantee Notice: All prototyping and custom AI development fees are paid upfront and are non-refundable. No guarantees of model performance, inference accuracy, compliance certification outcomes, or client business results are made or implied. Results depend on MSP execution, end-client data quality, and deployment environment. Stripe checkout requires a confirmation checkbox acknowledging these terms.

Related Capabilities Within the MSP Partners Program

Frequently Asked Questions

What is the difference between a Fleet prototype and custom AI development?
A standard Fleet prototype at $35,000 or $50,000 proves feasibility for a single use case with a working system and handoff documentation. Custom AI development at the $75,000 Compliance-Aware tier and above handles multi-model orchestration, custom fine-tuning, large-scale RAG, and compliance-grade inference pipelines that require purpose-built engineering beyond standard prototyping scope.
Does Petronella build user interfaces and web applications?
No. Petronella's custom AI work focuses on the infrastructure and model layer: private LLM deployment, RAG pipelines, agent frameworks, and compliance-grade inference. If the client also needs a front-end application, that scope is handled separately by the MSP's own team or a third party. Petronella provides the API endpoints and documentation that the application layer connects to.
Who owns the custom models and pipeline code?
Work-product ownership is defined in the statement of work. Default: the client owns all custom code and fine-tuned model weights. Petronella retains no copies beyond the engagement retention window. Base models remain under their original licenses. Petronella retains the right to reuse generic framework components that predate the engagement.
Can your team work inside our existing infrastructure during development?
Development and prototyping happens on Petronella's private fleet for security and efficiency. After the handoff, deployment to the client's production hardware is part of the Deployment stage. If the client has specific infrastructure requirements during the prototype phase, we accommodate them through secure VPN access or on-site work scoped in the statement of work.
How does pricing work for multi-phase custom AI projects?
Each phase is scoped and priced independently after a Discovery Call. Phase one is typically a Compliance-Aware prototype at $75,000 that validates the architecture and produces a working system. Subsequent phases for expanded scope, additional model integration, or production hardening are quoted separately. There are no volume discounts or cross-phase credits. Each phase delivers standalone value.

Scope Your Client's Custom AI Engagement

Book a free 30-minute Discovery Call to discuss the use case, data environment, compliance requirements, and which Fleet tier fits the engagement. Questions? Call (919) 348-4912 or contact us.

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