From first build to continuous improvement.
Agentrify covers the full life of an agent: designing it, choosing its models, testing it, improving it and proving what it is worth.
Multi-model, multi-agent by default.
Design systems of cooperating agents, and route each task to the model that suits it best, across providers.
- Visual and code-first design of agent teams: planners, specialists, reviewers
- A model gateway that routes by cost, quality, latency and data sensitivity
- Frontier, open-weight and small models, with automatic fallback
- Tool and data connectors with permissions set per agent
- Shared memory and context, scoped to what each agent needs
Illustrative. Routing policies are set by your team; no model provider is implied as a partner.
Test like it matters, because it does.
No agent should reach production, or change in production, without passing a test suite built from your own work.
Real-case suites
Build test sets from historical cases, with expected outcomes reviewed by your experts.
Edge cases and red-teaming
Probe unusual inputs, adversarial prompts and manipulated data before attackers or customers do.
Policy and regression checks
Confirm every version still respects limits, data rules and escalation paths, and has not got worse elsewhere.
Governed improvement, not unchecked self-modification.
Evolve finds ways to make an agent better, proves them on tests and presents them for approval. It improves prompts, tools, workflows, model choices and, where appropriate, fine-tuning. It never changes an agent's goals or authority.
Candidate changes
Generated from failures, reviewer corrections and cost data.
Tested on your suite
Each candidate is compared against the live version on the same cases.
Owner decides
A named person approves, with the evidence and the value impact in front of them.
Versioned release
Rolled out with monitoring, and reversible in one step.
Improve against the accounts, not just accuracy.
Every agent is linked to the business line it should move, its baseline, its full cost and its owner, using the Agent Value Ledger method developed by Kiros Intelligence Group.
- Revenue: conversion, retention, pricing
- Cost base: cost per case, rework, handling time
- Capital: days to collect cash, inventory
- Risk: losses and compliance cost, counted only with evidence
- Full cost includes models, supervision and assurance
Works with what you already run.
Designed to deploy in your cloud or ours, connect to your data and identity systems, and hand governance evidence to Praetor or your existing risk tools.
Deployment
Managed cloud or your own cloud environment.
Identity
Single sign-on and role-based access for builders and approvers.
Data
Connectors with least-privilege access per agent.
Governance
Evidence exported to Praetor, audit and risk systems.
Shape the platform with us.
We are working with a small number of organisations and engineering teams to finalise Agentrify before release.