Now available for early access

Smaller Models. Smarter Agents. Bigger ROI.

Autonomously simulate, fine-tune, and deploy enterprise-grade AI agents in days.

Up to 100xlower inference cost compared to frontier models on your tuned workflows
Private AI for every teamautonomous fine-tuning, no ML research required. Deploy custom models without a dedicated ML team.
Secure Modelspatent pending Cyber-aware Fine-tuning to ensure continuous compliance for your private AI
The thesis

Frontier APIs optimize for generality. PerceptEye optimizes for your business.

Every enterprise has a portfolio of repetitive, knowledge-intensive workflows that touch internal systems, software tools, and private data. Frontier AI services can do most of them, but using them directly is expensive, slow, leaks data, and produces unpredictable quality.

The alternative - training your own model - is the right move, but it stretches AI, machine learning, and data teams thin. Most of their time goes into plumbing rather than into the workflow itself. The talent is there. The hours are not.

PerceptEye gives those teams four specialist agents that handle the plumbing alongside them. A simulation engine gives everyone the same ground truth. Your team owns the model, the decisions, and the outcomes - they just get far more of each.

A model your team owns, that runs where you choose, that is measurably good at the work you care about - and keeps getting better, with the people you already have.
The Quartet Platform

Four agents. One closed loop.

Scout discovers the workflow. Compass designs the learning system. Ranger trains the model. Sherpa keeps it running reliably. Each agent is independently useful. Together, they form a self-improving system that extends your team's reach.

Scout

discovery

Maps your environment and surfaces the workflows that matter most

  • Leverages enterprise knowledge and observability telemetry
  • Identifies high-value automation opportunities
  • Creates a foundation for learning
N

Compass

learning design

Shapes how your models learn from real-world feedback

  • Bridges the gap between intent and outcome
  • Defines success for each workflow
  • Ensures data quality at scale

Ranger

training

Delivers production-ready models your team and customers can trust

  • Runs experiments autonomously with one touch
  • Optimizes for your specific use cases
  • Provides clear evaluation metrics

Sherpa

operations

Keeps your models running reliably at enterprise scale and budget

  • Maintains reliability within your policies
  • Monitors performance continuously
  • Balances speed, cost, and quality
Architecture

Inside your environment. End to end.

All four agents share one source of truth. Learning flows continuously from production back into training. Your data never leaves your environment.

Your Environment - Private Cloud - On-Premise
01 / SCOUT
Discovery
Maps your systems into testable workflows
02 / COMPASS
Design
Defines success and shapes training data
03 / RANGER
Train
Runs experiments and delivers models
04 / SHERPA
Deploy
Serves, monitors, and self-heals in production
Continuous Learning Loop
SHARED ENGINE
AgentSimulator
The shared ground truth
The compound effect

Greater than the sum of four agents.

// 01

Force Multiplier

Your AI, machine learning, and data teams keep the steering wheel. The agents handle the heavy lifting in parallel - so the same team ships several times more work.

// 02

Privacy

Every step happens inside your environment. The model is yours. Your data never leaves. Run in a public cloud, private cloud, on-premise, in a sovereign region, or fully air-gapped.

// 03

Reliability

Quality checks, drift detection, self-healing, and patent-pending cybersecurity-aware fine-tuning keep your model performing and passing the toughest security benchmarks.

// 04

Cost efficiency

A small, well-trained private model routinely outperforms a frontier service on the workflow it knows - at a fraction of the cost per request.

Adoption

Start with one agent. Or all four.

Each agent is independently valuable and designed to slot into the stack your team already runs. Ranger and Sherpa especially can be adopted on their own. Start where the pain is - bring in the rest when you're ready.

Scoutdiscovery
Map your systems, generate a library of candidate workflows, and make your existing agents observable. Valuable even if you never train a model.
entry point
Scout and Compassdiscovery and design
Turn that workflow library into a training-ready learning system your team can act on - cleaner data, clearer success signals, reproducible practice runs.
data team
Rangerstandalone training partner
Already have data and a goal? Hand them to Ranger. It picks the right base model, runs experiments, evaluates rigorously, and hands your team a model ready to ship. Pairs with any serving stack.
machine learning team
Sherpastandalone operations partner
Already have a trained model? Hand Sherpa the model and your target environment. It figures out the best way to run it, keeps it healthy, and lets your team focus on what to build next.
platform team
The full Quartetclosed loop
All four agents, plus AgentSimulator, plus the continuous learning loop. The platform becomes specifically good at your environment over time. Recommended when private AI is a core capability for the business.
recommended
A day in the life of AI practitioner

One workflow. Discovery to deployment.

Day 1 MON 09:14

Scout discovers

Maps the customer system, generates verified workflows

Day 1 MON 14:30

Compass designs

Defines success criteria, prepares training data

Day 2 TUE 02:48

Ranger trains

Runs experiments overnight, selects the best model

Day 2 TUE 09:02

Sherpa deploys

Validates quality, promotes to production

End of Week FRI 16:30

Quality drifts. Sherpa flags it. The loop closes automatically. Your team approves and moves on.

Partners & investors

Backed by builders. Trusted by platforms.

PerceptEye is proud to partner with the platforms pushing the frontier of AI infrastructure, and to be backed by investors who have been early to every major shift in enterprise software.

NVIDIA Inception Program
Google Cloud for Startups
Unusual Ventures

Your model. Your environment. Built by agents.

PerceptEye is a force multiplier for your AI, machine learning, and data teams - measurably better at a fraction of the cost of a frontier service on the work you actually do. Deploy one agent or the full team - on your terms, at your pace.