Security & Deployment

Deployed in your
environment. Full stop.

Sensitive data stays where it belongs. We deploy AI on your own infrastructure — cloud VPC, on-premises, or fully air-gapped — with zero data leaving your environment. Required for federal, healthcare, and financial workloads.

FedRAMP · HIPAA · Air-gapped capable
Why It Matters

Vendor lock-in is an AI
implementation risk.

Most AI consultancies are certified partners of one cloud provider. Their recommendation is predetermined. Ours is not.

Selection based on the problem, not the partnership

We evaluate each workflow independently. Complex reasoning tasks, multimodal needs, code generation, and sensitive data environments each have different optimal models. We match them correctly.

No pricing surprises from vendor dependency

When you are locked into one vendor, you absorb every price change and service interruption. Model-agnostic architecture lets us migrate to a better model when one becomes available without rebuilding your workflow.

Open-source for sensitive environments

Federal agencies, healthcare organizations, and financial firms often cannot send data to third-party API endpoints. We deploy open-source models on your own infrastructure — air-gapped if required.

Compliant with federal AI procurement requirements

OMB M-26-04 requires agencies to evaluate LLM vendors on unbiased AI principles, model cards, and bias evaluations. We perform this vetting for each model we deploy in government environments.

Model selection by workflow type (illustrative)
COMPLEX REASONING
Claude 3.5
92
GPT-4o
85
Gemini
80
MULTIMODAL / IMAGE + TEXT
Gemini
94
GPT-4V
87
CODE GENERATION
Codex/o1
91
Claude
88
AIR-GAPPED / SENSITIVE DATA
Llama 3
88
Mistral
82
The Stack

Four model categories.
Each selected for specific jobs.

We maintain active deployment experience with each category and evaluate new models as they release. What you see below reflects our current assessment — it updates as the field moves.

Claude 3.5 / 4
ANTHROPIC
Our primary reasoning engine. Claude excels at complex document analysis, multi-step reasoning, policy interpretation, and workflows requiring careful judgment with uncertainty. Particularly strong on federal compliance and legal document review tasks.
Complex reasoning Document analysis Policy interpretation Long context
Best for: Federal compliance review, contract analysis, complex research summarization, multi-document synthesis
Gemini 1.5 / 2.0
GOOGLE DEEPMIND
Our multimodal specialist. Gemini handles workflows that combine images, documents, and text — including form processing, diagram interpretation, and video analysis. Strong at structured data extraction from visual inputs.
Multimodal Image + text Form processing Video analysis
Best for: Document scanning workflows, mixed-media content processing, visual data extraction, form digitization
Codex / o1 / GPT-4o
OPENAI
Our code and structured-output specialist. Used where workflows require generating, validating, or transforming structured data — SQL queries, API integrations, data transformation pipelines, and automation scripts.
Code generation SQL / APIs Data transformation Structured output
Best for: Report generation pipelines, data integration workflows, automated testing, structured data extraction
Llama 3 / Mistral / Others
META · MISTRAL AI · COMMUNITY
Our choice for sensitive environments. Open-source models run on your own infrastructure — on-premises, in your VPC, or air-gapped. No data leaves your environment. Required for certain federal, healthcare, and financial workflows. We evaluate and fine-tune for your specific use case.
Air-gapped On-premises HIPAA / FedRAMP Fine-tunable
Best for: Sensitive data workflows, federal classified environments, HIPAA-governed healthcare, financial compliance
Decision Framework

How we choose the
right model for your workflow.

Every model selection follows the same evaluation framework. We document the rationale in the SOW so you understand exactly what you are buying and why.

🔒
Data sensitivity check
First question: can this data leave your environment? If not, open-source on your infrastructure. If yes, we proceed to capability matching.
→ Routes to: Open-source if restricted
🧠
Task type classification
Is the task primarily reasoning, multimodal, code generation, or structured extraction? Each category has a primary model candidate with documented benchmark scores.
→ Claude / Gemini / Codex / Llama
📊
Cost and latency modeling
For high-volume workflows, we model the cost per 1,000 operations across candidate models. If the best-performing model is 10x more expensive and a 90% model handles the task, we recommend the 90% model.
→ Cost per operation analysis
🧪
Validation against your data
We test 2–3 candidate models against a sample of your actual workflow data before recommending. Benchmark scores on public datasets often don't translate to your specific task.
→ Real data validation
📋
Federal compliance check
For government engagements, we evaluate the selected model against OMB M-26-04 Appendix A requirements: Acceptable Use Policy, Model Cards, bias evaluation methodology, and red-teaming results.
→ OMB M-26-04 compliance
🔄
Portability architecture
We build workflows with model abstraction layers. If a better model emerges — or pricing changes — you can swap the underlying model without rebuilding the entire workflow.
→ Future-proof design

Have a workflow in mind?
Let's find the right model.

Tell us what you're trying to automate. We'll recommend the right model, scope the engagement, and give you a fixed price before you commit to anything.

Start a Conversation