Smart Auto-Router
Set the model to “auto” and Core99 picks the best one for every prompt, by task, complexity, speed and cost.
Automatic failover · Pin a model anytime
The AI cloud
One API for every leading model, agents fine-tuned on your business, and AI that runs your processes. In one stack.
The platform
Each layer feeds the next: automations run on tuned agents, which run on the gateway. Enter at any layer.
Layer 1 · AI Gateway
One OpenAI-compatible endpoint and one key for the top providers, billed in pesos with CFDI.
Layer 2 · Fine-Tuned Agents
Fine-tuned agents for every department, trained on your terms, rules and tools.
Layer 3 · Agentic Automation
Layer 2 agents applied to your processes, connected to your data, tools and channels.
Layer 1 · AI Gateway
One OpenAI-compatible endpoint and one key. Switch models by changing the model name; migrating takes a base URL and a key.
from openai import OpenAI
client = OpenAI(
base_url="https://api.core99.io/v1",
api_key=os.environ["CORE99_API_KEY"],
)
resp = client.chat.completions.create(
model="auto", # or pin any model
messages=[{"role": "user", ...}],
)One endpoint. Every leading model.
Fast edge architecture
Close to every user and every model. Built for speed & always on.
Set the model to “auto” and Core99 picks the best one for every prompt, by task, complexity, speed and cost.
Automatic failover · Pin a model anytime
Token prices match each provider's own platform. Some models come with a discount.
One bill for every provider
CFDI-compliant invoicing (Mexican VAT), prepaid balance, spend limits and quotas per project or team.
Usage reports · Keys with roles and audit logs
Layer 2 · Fine-Tuned Agents
Upload curated examples: conversations that show the answers you want, tool calls included.
Training runs serverless. No GPUs or clusters to manage. Compare the new model right away.
The model ships through the same Core99 API. Keep improving it with reinforcement learning.
Fine-tuned on your terms, rules and tools. Agents work together as one multi-agent system, and are more accurate in their domain than a general model.
Prompting, then RAG. Fine-tune only when the numbers justify it. Our public calculator tells you which one pays off.
Managed service
For teams without AI staff
Self-serve platform
For technical teams
Start here
Prompting
Recommended
RAG
When the numbers justify it
Fine-tuning
Layer 3 · Agentic Automation
Agents connected to your data, tools and channels.
Layer 3 · Agentic Automation
Start on your own, or with our team by your side.
Sample project · HR
Problem: A company wants to automate how it selects candidates.
One agent to start:
Anyone on the team can set it up.
Many more HR processes:
We design, connect and launch it.
Local support in English and Spanish
The platform
Models, projects, agents, channels and billing in one place. No code needed.

Tell us what you are building. We will help you pick the right layer to start.