AI Integration for Tampa's Mission-Critical Sectors
As a veteran-owned SDVOSB, we build secure AI systems for MacDill contractors, BayCare and TGH-adjacent health systems, and the Franklin Templeton/Raymond James financial hub.
Off-the-shelf AI models fail in secure, regulated environments.
Public AI tools are a non-starter for Tampa's core industries. Sending sensitive data—be it CUI for a SOCOM contract, PHI from a hospital system, or proprietary financial data—to a third-party API is an unacceptable security risk and a compliance violation. These generic models can't access your private data, leading them to provide useless or fabricated answers. They lack the security, context, and reliability required for mission-critical work. Without a private, purpose-built system, AI is just a liability.
- Public LLMs like GPT-4 process data on external servers, violating CMMC/ITAR.
- Generic models hallucinate answers when querying classified or proprietary documents.
- Standard AI integrations lack HIPAA-compliant data handling for patient records.
- Automation attempts fail without fine-tuning on specific financial claims or intelligence reports.
Deploying secure, on-prem or VPC-hosted AI that works with your data.
- STEP-01
Environment & Compliance Scoping
We map your data security requirements—CMMC, HIPAA, or SEC—to a specific deployment architecture, either on-premise or in a secure Virtual Private Cloud (VPC). No data leaves your operational control.
- STEP-02
Secure Data Ingestion & Indexing
We connect to your existing data sources, from SharePoint document libraries to SQL databases, creating a secure, indexed vector store for Retrieval-Augmented Generation (RAG) that respects all existing access controls.
- STEP-03
Model Selection & Fine-Tuning
We select and fine-tune appropriate models on your specific document sets, reducing hallucinations and ensuring outputs are grounded in your proprietary data. We choose the right tool for the mission, not the most hyped one.
- STEP-04
Workflow Integration & Guardrails
The AI is integrated directly into your tools like Zendesk, Salesforce, or custom internal platforms. We build strict output guardrails to prevent data leakage and ensure operational relevance for your team.
from langchain_community.vectorstores import FAISS
from langchain_community.embeddings import HuggingFaceEmbeddings
from langchain_text_splitters import RecursiveCharacterTextSplitter
# Use a locally-run model for embeddings to prevent data leakage
# This model runs on your hardware, not a third-party API.
model_name = "sentence-transformers/all-mpnet-base-v2"
model_kwargs = {'device': 'cpu'}
encode_kwargs = {'normalize_embeddings': False}
embeddings = HuggingFaceEmbeddings(
model_name=model_name,
model_kwargs=model_kwargs,
encode_kwargs=encode_kwargs
)
# Load documents from a secure, local source
with open("secure_docs/project_brief.txt") as f:
project_docs = f.read()
text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=100)
docs = text_splitter.split_text(project_docs)
# Create a local vector store for retrieval
db = FAISS.from_texts(docs, embeddings)
# The 'db' object can now be used for secure, local similarity searches
retriever = db.as_retriever()A Retrieval-Augmented Generation (RAG) pipeline using a local embedding model, ensuring proprietary or classified data never leaves the client's secure network perimeter.
Field FAQ.
→ How do you handle classified or CUI data for MacDill contractors?
We deploy models entirely within your designated environment, whether it's an on-premise server or a GovCloud instance. All data processing, from embedding to generation, occurs inside your security boundary, meeting CMMC 2.0 and other federal requirements. We never use public APIs for sensitive workloads, ensuring full data control and security.
→ Is your firm eligible for SDVOSB set-aside contracts?
Yes. VooStack is a CVE-certified Service-Disabled Veteran-Owned Small Business (SDVOSB). This makes us eligible for federal sole-source and set-aside contracts, providing a streamlined procurement path for agencies at MacDill, SOCOM, and other federal entities in the Tampa area seeking specialized technical partners.
→ Can you build HIPAA-compliant AI for healthcare systems?
Absolutely. We achieve HIPAA compliance by ensuring no Protected Health Information (PHI) is processed by third-party services. We implement solutions within your private cloud or on-premise infrastructure and can sign a Business Associate Agreement (BAA). This is critical for automating patient record analysis or claims processing securely.
→ What does a typical AI integration project timeline look like?
A typical project moves from discovery to a production-ready pilot in 3 to 6 months. This includes a 2-4 week scoping phase, a 6-8 week data integration and model tuning phase, and a final 4-6 week period for workflow integration and user acceptance testing. The complexity of the data sources dictates the final timeline.
→ Do we need our own data scientists to work with you?
No. We provide end-to-end service with our team of senior engineers. We handle the entire technical lifecycle, from infrastructure setup and data engineering to model fine-tuning and API integration. We deliver a finished capability that your existing teams can use without needing specialized AI expertise.
→ What kind of ROI can we expect from automating document analysis?
While specific ROI varies, clients typically see significant efficiency gains. For example, automating the review of intelligence reports, financial filings, or insurance claims can reduce the time analysts spend on manual extraction by 80-90%. This frees up your most skilled personnel for higher-value strategic analysis rather than routine data processing.
→ How do you ensure the AI doesn't 'hallucinate' or provide incorrect information?
We primarily use Retrieval-Augmented Generation (RAG), which grounds the AI's responses in your own verified documents. By forcing the model to cite its sources from your internal knowledge base, we dramatically reduce the risk of hallucination. We also implement strict prompting and output validation to ensure factual accuracy and operational relevance.
→ What's the difference between your service and just buying a ChatGPT Plus subscription?
Consumer tools like ChatGPT send your data to external servers for processing, creating massive security and compliance risks for any serious organization. Our solutions are private, secure, and tuned on your data. We build systems that operate exclusively within your network, giving you full control and ownership over your data and the AI's outputs.
Continue recon.
Our AI Services
Learn about our full range of AI integration and custom software development capabilities.
REL-02Federal & Regulated Work
See how we've implemented secure, compliant solutions for clients in demanding environments.
REL-03Veteran-Owned Mission
Understand our background as an SDVOSB and our commitment to operational excellence.
REL-04Schedule a Scoping Call
Get in touch to discuss your specific AI integration needs in the Tampa Bay area.
Deploy AI That Meets Tampa's Security Standards.
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