Agents that hold up in production.
AI engineering at VectoRise means production systems: voice and text agents, retrieval pipelines, evaluation, and the operator consoles that keep them observable after launch.
We treat models as infrastructure. That includes telephony-grade voice agents, guardrails around tool use, and the unglamorous work of recordings, supervision, and failover so a conversation does not die mid-sentence.
01
Voice agents
Real-time speech in and speech out, barge-in, and outbound calling across major telephony providers, with an operator UI for scripts, numbers, and live supervision.
02
Agentic workflows
Tool-using agents with explicit permissions, evaluation, and logging. Autonomy is a design choice, not a default.
03
Retrieval and evaluation
RAG pipelines with measurable quality, not a vector store and a prayer. Eval loops before you scale call volume.
04
Operator platforms
Dashboards, recordings, and admin controls so the business can run the system without opening a terminal.
The operating language for this practice: how we scope the work and what we leave in the room.
Straight answers before a scoping call.
Both. Our voice work includes real-time calling, interruption handling, and operator tools. Text and tool-using agents follow the same production bar.
No. The orchestration, telephony, and operator layer are yours. Models are swappable components behind that.
Explicit tool permissions, logging, and the same posture thinking we apply in Aegis: if an agent can execute code or reach the public internet, that should be a conscious grant.
Book a scoping call.
A short conversation is enough to see whether we should work together.