Technology Ecosystem
Cortex Texas AI selects and combines AI models, orchestration frameworks, knowledge systems, software technologies, integrations and infrastructure according to the needs of each project — not a fixed stack.
Approach
Cortex Texas AI evaluates every model, framework and platform against the requirements of the system it's going into — not according to what's newest or most talked about. The same evaluation criteria apply regardless of vendor.
The Stack
By Category
The foundation models and AI platforms Cortex builds and integrates against.
The frameworks that coordinate multi-step reasoning, tool use and agent workflows.
Retrieval, vector search and knowledge infrastructure that ground AI in your own data.
Telephony, speech-to-text and text-to-speech technology for voice-based AI interaction.
The backend, frontend and integration technologies Cortex builds production systems with.
The databases and storage systems AI-enabled business applications are built on.
Selected Examples
Process
Technology selection follows the business system's requirements, not the other way around.
What the system actually needs to do.
Accuracy, latency, cost, security and data constraints for that requirement.
Candidate models, frameworks and platforms assessed against those constraints.
A working prototype tests the choice against real data and workflows.
The validated technology is built into the production system.
Composition
Responsible Engineering
Systems and credentials are scoped to only what a given workflow needs.
Only the data a task genuinely requires is sent, stored or logged.
Requests, model calls and automated actions can be logged and traced.
Application logic is kept separable from any single model or platform provider.
Systems are built to be understood, extended and handed off, not just shipped.
Integrations use authenticated, scoped and auditable connection methods.
Access to model calls and outputs is limited to the systems and roles that need it.
Related
How AI call routing, intake and appointment scheduling help medical, legal and accounting practices answer every call, capture the right details and book appointments, while staff keep control.
Read articleTraditional automation follows fixed rules; AI agents reason about a goal and decide what to do. Here's how the two actually differ, and when each one is the right fit for a business process.
Read articleTimelines vary with scope, but a focused custom AI application commonly takes a few weeks from requirements to a working production version, while larger multi-system projects take longer.
Read articleTalk with our engineering team about which models, frameworks and infrastructure actually fit your system.