Define the system
Map the workflow, data, constraints, risks, and success metrics before choosing models or tools.
Services
AI systems designed around production reality.
Engence builds AI agents, computer vision, and custom AI/ML systems with the evaluation, integration, and deployment work needed to run them in real business environments.
01Learn
AI Agents
Agents that operate inside real workflows with permissions, audit trails, human review, and measurable reliability.
- Workflow automation with human-in-the-loop checkpoints
- Tool integrations across CRMs, support desks, internal systems, and knowledge bases
02Learn
Computer Vision
Detection, recognition, inspection, and monitoring systems for environments where cameras become operational sensors.
- Detection and recognition pipelines tuned to real environments
- Inspection and alerting systems with measurable false-positive controls
03Learn
Custom AI/ML
Custom models, retrieval systems, pipelines, and evaluations for problems that off-the-shelf tools cannot solve cleanly.
- Retrieval, ranking, classification, extraction, and prediction pipelines
- Model evaluation tied to product and operational metrics
Engagement path
A simple structure for uncertain AI work.
Every build starts by reducing ambiguity. We define the workflow, prove the behavior, and only then expand the system.
Prototype the critical path
Build the smallest working slice that proves the behavior and exposes the failure modes.
Engineer for production
Add integrations, evaluation, observability, fallbacks, permissions, and deployment controls.
Operate and improve
Monitor quality, review edge cases, tune thresholds, and iterate from real production feedback.
Have a workflow, model, or vision system that needs to ship?
Email the problem, the current system, and what a useful first production version would need to prove.
Helpful context
- What workflow or decision are you trying to improve?
- What systems, data, or cameras does the AI need to connect with?
- What would make the first production version successful?