The Five AI Providers We Actually Use

There is a version of this conversation that goes, "which AI model is best?" That is the wrong question for most business owners. The right question is which provider is best suited for the specific job you are trying to do, and which one you can actually rely on when the tool is in production at 2 AM.

We work across all five major providers. Here is what that looks like in practice.

Why we do not pick one and stop

Every AI provider has a different center of gravity. Some are stronger at reasoning through dense documents. Others are faster at structured data extraction. Some have better fine-tuning ecosystems. Others have the widest model variety for different cost tiers.

Locking a client into a single provider is a delivery decision dressed up as a strategic one. It optimizes for our convenience, not theirs. We use the right tool for the job, and we keep the architecture clean enough that swapping a model layer does not require rewriting the system.

OpenAI

OpenAI has the broadest developer ecosystem of any AI company right now. The API is well-documented, the tooling is mature, and the model variety gives you a real cost curve to work with. We use OpenAI heavily for voice workflows, because Whisper (their speech-to-text model) integrates cleanly with the real-time pipelines we build on Vapi.

For client deployments that need wide plugin compatibility or where the team has existing OpenAI API familiarity, OpenAI is usually the starting point.

Anthropic

Anthropic's models are consistently strong at nuanced reasoning and at following complex instructions without drifting. When we build intake workflows where the AI has to hold a multi-turn conversation, respect edge cases, and stay within a defined role, Anthropic's models tend to stay in lane better than the alternatives.

We also use Anthropic on anything that touches regulated or sensitive data, partly because their approach to safety and their documented research gives our clients more confidence in the audit trail.

xAI (Grok)

xAI is the youngest player in the group, but the Grok models have moved fast. The real-time data access is the actual differentiator here. For clients who need to pull live market data, recent news, or current pricing into a workflow, Grok's live web access removes a whole integration layer that you would otherwise have to build and maintain yourself.

We use xAI selectively, but for the right use cases it saves significant architecture time.

Google (Gemini)

Gemini's multimodal capability is the most mature in the group. If the workflow touches images, documents with mixed content, or video, Gemini is usually where we start. Google Cloud's native integration also matters for clients who are already deep in the Google ecosystem and do not want to move data across providers.

On large-context tasks, Gemini's window is competitive, which matters when you are working with long contracts, dense reports, or large product catalogs.

Meta (Llama)

Llama is the open-weights option, which means it can be run on your own infrastructure. For clients with strict data residency requirements or who need to avoid sending sensitive content to any third-party API, a hosted Llama deployment is the answer.

We use Llama for on-prem scenarios, HIPAA-adjacent workflows where the client wants full custody of the data, and situations where the volume of API calls makes third-party pricing unworkable at scale.

How we actually choose

The decision tree looks like this:

• Real-time data access needed? Start with xAI.
• Multimodal or heavy document work? Start with Google.
• Complex multi-turn conversations or regulated environment? Start with Anthropic.
• Voice pipeline or wide plugin ecosystem? Start with OpenAI.
• On-prem, data residency, or high-volume at scale? Start with Meta/Llama.

Most production deployments end up using more than one. A voice agent might use Whisper for transcription, route the transcript to Anthropic for reasoning, and log the result to a CRM workflow via Zapier. The provider is one layer in a system, not the whole system.

The point is not to have an opinion about which company is best. It is to know the catalog well enough to use the right piece in the right place. That is what one technical partner looks like when it actually works.

If you want to know which combination makes sense for your specific workflow, that is what the strategy session is for. Book one at salvus-ai.com.