AI Prototyping Services For Regulated Industries
Petronella Technology Group is a Raleigh, NC AI prototyping company that has been delivering regulated-industry technology since 2002. We build working AI prototypes on our own private datacenter cluster, run them against your real data, and deliver a production hardware blueprint sized to your actual workload. No cookie-cutter SaaS. No public-cloud lock-in. No "we will figure scaling out later."
What you get when you hire us
A snapshot of the engagement, the deliverables, and the kind of organization this is built for. If your team is already past the "what is AI" stage and is choosing a partner, this is the page you want.
The Petronella AI prototyping engagement at a glance
- A working prototype on our private AI cluster, not a slide deck. We build, benchmark, and stress-test against your real data inside a controlled boundary in Raleigh, NC. NDAs and BAAs signed before any data moves.
- A production hardware blueprint sized to real-world load. Server count, GPU model, memory, storage, network topology, deployment options (on-prem cluster, colo, hybrid, regulated-cloud), 1-year and 3-year total cost of ownership.
- Three engagement tiers, scoped on a discovery call. Discovery sprint, prototype build, and production blueprint - each priced after a 30-minute conversation about your data, regulatory frame, and timeline. No surprise invoices.
- Typical timeline 6 to 12 weeks. Two weeks for the discovery and assessment, four to eight weeks for the prototype, two weeks for the blueprint. Clear weekly checkpoints with your sponsor.
- Built for regulated verticals. Engineering and AEC firms, healthcare under HIPAA, defense contractors under CMMC L1, L2, and L3, finance, and legal. Audit-ready logging and access control standard.
- You own the code, the model, the data, and the blueprint. No "platform tax." We hand off documented artifacts your team can run, audit, and extend without us if you want to.
- Same firm runs the production deployment if you want. Petronella has been an MSP since 2002. Prototype on Monday, full managed operations on the same engineering bench when you scale.
What our AI prototyping engagement delivers
Six concrete artifacts at the close of a typical engagement. No hand-waving, no "report-only" deliverables, no homework left on your desk.
1. A working prototype against your real data. Not a sample dataset, not a demo on a laptop, not a cloud SaaS trial. We build the prototype on Petronella's private AI cluster in Raleigh, ingest a representative slice of your production data under NDA (and BAA where HIPAA applies), and run it under realistic load. You see the output, you see the failure modes, you see how it performs when ten people use it at once instead of one.
2. A real-data benchmark report. Throughput, latency at p50/p95/p99, GPU memory pressure, data pipeline I/O, integration friction with your upstream and downstream systems. We measure six bottleneck classes (compute saturation, GPU memory ceiling, data pipeline I/O, inference latency under concurrency, integration friction, observability gaps) and flag which ones will bite at production scale.
3. Integration scaffolding for your stack. Working hooks into the systems the prototype actually needs to talk to: ERP, document store, CRM, identity provider, ticketing system, whatever your environment runs. We use service accounts, API keys, and access patterns that match how production will work, not throwaway integrations that pretend the API is unauthenticated.
4. A regulatory and security scoping document. Where the data lives, who can see it, what the audit log captures, how access is revoked, how the model and the prompt history are stored, what residual risks remain. Aligned to HIPAA, CMMC L1 / L2 / L3, NIST 800-171, NIST 800-53, GLBA, or SOC 2 depending on your environment. This document is the one your compliance officer or general counsel signs off before you fund the production build.
5. A production hardware and architecture blueprint. The deliverable that separates a prototype from a production plan. Server count and form factor, CPU and RAM, GPU model and quantity (sourced through the NVIDIA Elite Partner Channel for NVIDIA Systems where applicable), storage tiers, network topology, deployment topology (on-prem cluster, colo, hybrid, regulated-cloud enclave), an operations runbook, and a 1-year and 3-year total cost of ownership model so finance can compare against alternatives.
6. A go / no-go recommendation, in writing. If the prototype shows the project should not proceed in its current form, we say so. We will tell you the cheaper path, the smaller scope, the off-the-shelf alternative, or the "wait six months and re-evaluate" recommendation when that is the honest answer. A prototype that prevents a multi-million-dollar mistake is the highest-value outcome, not the worst one.
| Deliverable | Included in a typical Prototype tier | Out of scope (separate engagement) |
|---|---|---|
| AI Readiness Diagnostic (data, integration, regulatory scoping) | Included | - |
| Working prototype on Petronella private AI cluster | Included | - |
| Real-data benchmark and bottleneck report | Included | - |
| Integration scaffolding (up to 3 upstream / downstream systems) | Included | 4+ systems scoped separately |
| Regulatory and security scoping document | Included | - |
| Production hardware and architecture blueprint | Included | - |
| Full security audit (NIST 800-171 / 800-53) | Out of scope | Separate CMMC engagement |
| Production deployment and managed operations | Out of scope | Separate managed services contract |
| End-user training and change management | Out of scope | Separate Statement of Work |
| 24/7 incident response on production workload | Out of scope | Separate cyber-security retainer |
Assess, Prototype, Blueprint
Every Petronella AI prototyping engagement runs through the same three stages. This is the high-level summary. The full methodology, including the bottleneck taxonomy and hardware sizing model, lives on our methodology pillar page.
Stage 1: Assess
Two weeks. AI Readiness Diagnostic. We map the opportunity, the data state, the integration paths, the regulatory constraints, and the success criteria. We confirm the project is worth prototyping before you fund the build. Deliverable: a written diagnostic with go / no-go recommendation, scope, and price for Stage 2.
Stage 2: Prototype
Four to eight weeks. We build the working prototype on Petronella's private AI cluster, ingest a representative slice of your data under NDA / BAA, and stress-test against six classes of scaling bottleneck. Deliverable: a working artifact, telemetry, a benchmark report, and a regulatory scoping document.
Stage 3: Blueprint
Two weeks. We translate prototype telemetry into a production hardware and architecture spec: server count, GPU model and quantity, storage, network, deployment topology, ops runbook, 1-year and 3-year total cost of ownership. Deliverable: the document your finance and engineering teams use to fund and build production.
Read the full 3-stage methodology
The bottleneck taxonomy (compute saturation, GPU memory ceiling, data pipeline I/O, inference latency under concurrency, integration friction, observability gaps), the hardware sizing model, and the FAQ for each stage live on our methodology pillar.
Pricing and engagement tiers
Three commitment levels. From-pricing reflects typical scope. Final scope and price are confirmed on a 30-minute discovery call so the proposal matches your specific bottleneck, data volume, integration count, and regulatory framework.
Discovery Sprint
Scoped on a discovery call
Final price confirmed after a 30-minute conversation about your data, regulatory frame, and timeline.
- AI Readiness Diagnostic: data, integration, regulatory scoping
- Opportunity confirmation with go / no-go written recommendation
- Success-criteria definition agreed with your sponsor
- Stage 2 scope, deliverable list, and fixed-price proposal
Prototype Build
Scoped on a discovery call
Scope is driven by data volume, integration count, and regulatory framework. Fixed-price proposal issued after Stage 1 Discovery Sprint.
- Working prototype on Petronella's private AI cluster
- Real-data benchmark and bottleneck report (six classes)
- Integration scaffolding for up to 3 upstream / downstream systems
- Regulatory and security scoping document (HIPAA / CMMC / NIST aligned)
- NDA and BAA signed before any data moves
- Weekly checkpoints with your sponsor and engineering lead
Production Blueprint
From custom quote
Scope confirmed after Stage 2. Driven by deployment topology and 3-year operations footprint.
- Production hardware sizing: server count, GPU, memory, storage, network
- Deployment topology: on-prem, colo, hybrid, or regulated-cloud enclave
- Operations runbook for your internal team or a Petronella retainer
- 1-year and 3-year total cost of ownership model
- Optional: warm hand-off to Petronella managed operations
All tiers exclude production deployment, end-user training, and ongoing managed operations. Those are separate engagements priced after the blueprint is delivered, so finance has a hard number before signing the next Statement of Work. We accept ACH, wire transfer, and credit card. NDAs and BAAs are signed before any data moves.
Who we serve
We focus on regulated industries because that is where private AI infrastructure, contractual residency, and audit-ready logging actually matter. Below is a per-vertical view of the kinds of prototype engagements we run.
Engineering and AEC firms
Architecture, engineering, and construction firms have years of project files, RFI history, structural calculation libraries, CAD revisions, and specification documents that internal teams routinely re-derive from scratch because the search tools never worked. Private AI prototypes here typically focus on RFI triage, specification drafting against historical projects, code-compliance pre-check, and quote / scope-of-work generation. We have an active engineering-firm client (Catlin) on this track. Trade-secret and IP protection is the unmovable constraint, which is why a Petronella private cluster engagement fits where a public-cloud SaaS trial does not.
Healthcare
Hospitals, specialty practices, dental groups, and digital-health vendors operating under HIPAA need ePHI to stay inside a Business Associate Agreement boundary. Common prototype scopes: clinical-note summarization against an internal EHR slice, prior-authorization drafting, billing-code pre-check, and patient-message triage. We sign BAAs before any data moves, run the prototype against a de-identified or BAA-covered slice, and deliver an audit-log model your compliance officer can sign off.
Defense and aerospace
Prime and sub-tier defense contractors handling Federal Contract Information (FCI) under CMMC Level 1, Controlled Unclassified Information (CUI) under CMMC Level 2, and the higher-bar workloads under CMMC Level 3 cannot move CUI into a public AI tool without violating DFARS 252.204-7012. Petronella's private cluster engagements run inside a CMMC-aligned enclave, with FIPS-validated cryptography, separated key custody, and an audit log structured for a CMMC assessor. Common scopes: SSP and POAM assistance, technical writing against historical contract files, supplier-package pre-screen.
Finance and accounting
Banks, credit unions, RIAs, accounting firms, and finance functions inside larger enterprises run a tight perimeter on customer-account data under GLBA, SOX, and SOC 2. Common prototype scopes: account-reconciliation triage, KYC / AML document review, internal-policy Q&A, and audit-trail generation for finance teams. The deliverable everyone wants is the same: an internal AI tool that does not leak customer-account data into a public model and that produces a logged record of every prompt and response.
Legal
Law firms, in-house legal departments, and IP boutiques cannot stream privileged client communication through a third-party AI tool without raising serious privilege and ethics-rule questions. Common prototype scopes: brief drafting against firm precedent, contract-clause comparison, deposition transcript triage, and matter-intake summarization. The combination of privilege, conflict-check discipline, and bar-rule compliance is exactly the kind of constraint a private-cluster engagement is designed for.
If you are a solo inventor, founder, or IP attorney
This commercial engagement model is built for organizations that can absorb a 3-stage 6-figure-class engagement. Solo inventors, lone founders, IP attorneys, R&D scientists, and trade-secret holders who want a private AI deployment to keep an invention or patent thesis off ChatGPT, Gemini, and Claude have a smaller-scoped fit: a focused private AI deployment, not a full Assess, Prototype, Blueprint engagement.
See our private AI options for IP-protective founders, inventors, and patent holders →
Why hire Petronella for AI prototyping
Real credentials, no fabricated client counts, no "trusted by 500 enterprises" claims. Here is what is actually behind the firm.
The shortest version of the differentiator: most AI prototyping firms hand you a slide deck and a cloud-provider invoice. Petronella hands you a working prototype on a private cluster, a real-data benchmark, a regulatory scoping document, and a hardware blueprint sized to your real load. If you ever decide to run the production workload on your own infrastructure, you have everything you need to do so. If you decide to keep it on Petronella's cluster, the engineering team that built the prototype is the same one that runs operations. This is the model we have run since 2002 and it does not require you to bet a strategic AI program on a cloud bill that grows on a curve no one inside your finance team modeled.
What an engagement looks like, week by week
A typical 8-week prototype engagement. Discovery and Blueprint are bracketed at 2 weeks each on either side. Below is what happens, who is involved, and what we need from your team.
Weeks 1 - 2: Stage 1 Assess
AI Readiness Diagnostic
Sponsor kick-off. Data and integration discovery. Regulatory scoping. Success-criteria definition. NDA in place. We deliver a written diagnostic, go / no-go recommendation, and a fixed-price proposal for Stage 2. Your involvement: 4 to 6 hours of stakeholder interviews and document access provisioning.
Week 3: Stage 2 Prototype kick-off
Architecture, access, BAA
BAA signed if HIPAA applies. Petronella provisions a project-scoped enclave on the private cluster. Your team provisions service accounts and API keys. Data slice transfer over a controlled channel. End-of-week checkpoint with sponsor.
Weeks 4 - 5: Build vertical slice
End-to-end happy path
Petronella engineers build the first working vertical slice end-to-end on real data. Output review with your sponsor on Friday of Week 5. Common adjustments: tone, output format, integration error handling. We document them and re-baseline before stress testing.
Weeks 6 - 7: Stress test, benchmark, integrate
The bottleneck hunt
Concurrent-load benchmark. Throughput, latency at p50/p95/p99, GPU memory pressure, data pipeline I/O, integration friction. Telemetry captured for the blueprint. Integration scaffolding wired to up to 3 upstream / downstream systems. Mid-week and end-of-week checkpoints.
Week 8: Stage 2 close
Walkthrough and scoping document
Working prototype walkthrough with your sponsor and engineering lead. Benchmark report delivered. Regulatory and security scoping document delivered. Stage 3 scope and timing agreed. Your team has everything needed for an internal go / no-go on production.
Weeks 9 - 10: Stage 3 Blueprint
Production hardware and architecture
Sizing model from prototype telemetry. Hardware blueprint: servers, GPU, memory, storage, network. Deployment topology recommendation. Operations runbook. 1-year and 3-year total cost of ownership model. Final readout to your sponsor, finance, and engineering leadership.
Decisions are made on Friday checkpoints by your sponsor with input from engineering and (where applicable) compliance and finance. We need: a single sponsor with budget authority, an engineering lead who can grant data and integration access, and (if HIPAA / CMMC applies) a compliance contact who can co-sign the BAA and the regulatory scoping document. Most engagements run with a sponsor commitment of 2 to 4 hours per week. Engineering involvement is heaviest in Weeks 1 and 3 (access provisioning) and Week 8 (walkthrough).
AI prototyping services FAQ
The questions every Director of Engineering, VP of IT, or Innovation lead asks before writing a Statement of Work. If yours is not here, send it on the discovery call.
How much does an AI prototyping engagement cost?
Every engagement is scoped on a 30-minute discovery call so the price reflects your actual data volume, integration count, regulatory framework, and timeline. Stage 1 Discovery Sprint is the consistent starting point and ends with a fixed-price proposal for Stage 2 Prototype Build. Stage 3 Production Blueprint is custom-quoted after Stage 2 because the right scope depends on the actual deployment topology and the 3-year operations footprint. Book the call here and we will scope and price your engagement together.
How long until we have a working prototype?
Typical engagement is 6 to 12 weeks end-to-end: 2 weeks of Discovery (Stage 1), 4 to 8 weeks of Prototype Build (Stage 2), 2 weeks of Blueprint (Stage 3). The first end-to-end working vertical slice usually shows up at the end of Week 5 (Week 3 of Stage 2). If you only need the Prototype and not the Blueprint, that compresses the calendar by two weeks. Faster than 6 weeks is rare and usually a sign the discovery work was skipped, which is the failure mode we are most careful to avoid.
Do you sign NDAs and BAAs?
Yes to both, every engagement, before any data moves. NDA is signed at the start of Stage 1 Discovery. BAA (Business Associate Agreement under HIPAA) is signed before any ePHI data slice is transferred for Stage 2. We can work from your firm's standard paper or use a Petronella-provided template, whichever your legal team prefers. We have run this signing track since the firm was founded in 2002.
Can you work with HIPAA-protected data?
Yes. Workflow: BAA signed before data movement, ePHI slice transferred over a controlled channel, prototype runs inside a project-scoped enclave on Petronella's private AI cluster (no public model API in the data path), full audit log on every prompt and response, role-based access with revocation tested. The regulatory and security scoping document delivered at end of Stage 2 is structured exactly for your compliance officer to sign off. If your covered entity requires a specific data-handling addendum, we work to that.
Is the prototype hosted on your infrastructure or ours?
The prototype runs on Petronella's private AI cluster in Raleigh, NC during Stage 2. This is intentional: the entire point of a prototype is to find the bottlenecks under realistic load without you having to procure hardware first. The Stage 3 Blueprint then specifies whether the production workload should run on your on-prem cluster, in a colo facility, in a hybrid topology, or in a regulated-cloud enclave. You choose. Many of our engineering, healthcare, and defense clients choose on-prem or colo for production for the same data-sovereignty reasons that drove them to Petronella in the first place.
What happens after the prototype - do we own the code?
Yes. You own the code, the model weights (where the prototype uses an open-weights model), the training and prompt history, the configuration, and the blueprint document. We hand off documented artifacts your engineering team can run, audit, and extend without us. We do not run a "platform tax" model where leaving Petronella means rewriting the project. If you decide to keep operations with Petronella, that is a separate managed-services contract that re-uses the same code, not a re-platforming.
Do you handle production deployment and ongoing operations?
Yes, but as a separate engagement. The prototype and blueprint engagements are scoped to deliver a buildable production plan; production deployment and 24/7 operations are scoped after the blueprint is delivered so finance has a hard number to compare. Petronella has been a managed service provider since 2002, so the same engineering bench that built the prototype can run the production workload. Many clients choose that route. Others take the blueprint and have an internal team build and run, which is equally valid. See our managed IT services for the operations engagement model.
How do you compare to other AI prototyping firms?
Three comparison points buyers usually ask about. First, infrastructure: many AI prototyping firms run prototypes on a public cloud account, which is a serious problem for HIPAA, CMMC, and IP-sensitive workloads. Petronella runs on a private AI cluster in Raleigh, NC. Second, deliverables: most prototyping firms deliver a working demo and a slide deck. Petronella delivers a working prototype, a real-data benchmark report, a regulatory scoping document, and a production hardware blueprint with TCO. Third, lifecycle: most prototyping firms hand off and disappear. Petronella has been a managed service provider since 2002, so if you want the same firm to run operations on the workload that goes live, the contract surface is one phone call, not a vendor handoff.
Do you support CMMC Level 1, Level 2, and Level 3 environments?
Yes, all three CMMC levels. Petronella is a CMMC-AB Registered Provider Organization (RPO #1449) and the team is whole-team CMMC-RP certified. Prototype engagements running against Federal Contract Information (CMMC Level 1), Controlled Unclassified Information (CMMC Level 2), and the higher-bar CMMC Level 3 workloads run inside a CMMC-aligned enclave with FIPS-validated cryptography and an audit log structured for a CMMC assessor. We routinely co-deliver prototype work alongside our CMMC compliance practice when both threads run in parallel.
What if the prototype shows the project should not proceed?
We tell you, in writing, with the data behind the recommendation. A go / no-go recommendation is a standard deliverable on every engagement. If the bottleneck report shows the workload cannot scale within the budget you have, or that an off-the-shelf SaaS would meet the same need at one-tenth the cost, or that a wait-and-re-evaluate posture is the honest call, we say so. A prototype that prevents a multi-million-dollar mistake is the highest-value outcome of the engagement, not the worst one. About one in seven engagements ends with a partial or full no-go recommendation; in every case, the client tells us afterward that the discovery was worth it.
Can we start with just the Discovery Sprint and decide on Prototype later?
Yes, that is the most common starting point. Stage 1 Discovery Sprint is two weeks of AI Readiness Diagnostic work and ends with a written go / no-go recommendation and a fixed-price proposal for Stage 2. If you decide not to proceed, you keep the diagnostic, the scoping document, and the recommendation, and we shake hands on a job well done.
Where is your team located?
Petronella is headquartered at 5540 Centerview Dr., Suite 200, Raleigh, NC 27606. The engineering bench, the private AI cluster, and the CMMC-aligned enclave operations are all on-shore in North Carolina. We work with clients across the United States and run engagements remotely with on-site visits when an engagement justifies them. For regulated-industry buyers, on-shore engineering and on-shore data residency are usually the table stakes that bring them to us in the first place.
The next step is a 30-minute discovery call
Tell us about the workload, the data, the regulatory frame, and the timeline. We will tell you whether a Discovery Sprint is the right next step, what the Prototype scope likely looks like, and what a realistic price range is for your specific situation. No pressure. No proposal until both sides confirm fit.