Independent performance management for AI agents

Know whether your AI agents are delivering.

Agentometry independently measures the efficacy, efficiency and control of enterprise AI agents — from development into production — and tells leaders which agents to scale, improve, constrain or stop.

Efficacy
Does it do the job?
Efficiency
What does it truly cost?
Control
Is it within authority?

Agent estate — live view

Production

Claims Triage

Scale

Motor claims

Efficacy91
Efficiency88
Control94

Customer Service

Improve

Tier-1 resolution

Efficacy76
Efficiency92
Control83

Procurement

Constrain

Supplier onboarding

Efficacy89
Efficiency61
Control72

Agents measured

14

Cost / successful outcome

£2.41

Control breaches (30d)

3

The gap

Enterprises are deploying agents faster than they can judge them.

Agents are being placed into claims, service, procurement and research processes at speed. Engineering teams can see what an agent did. Nobody can yet give the executive an independent answer to a simpler question: is this agent a good worker for the business function it has been given?

What today’s tools show

What leaders need to decide

Traces, spans and token counts
Business outcomes completed correctly, end to end
Model evals on curated test sets
Live performance against the function the agent was hired to do
Infrastructure cost dashboards
Fully loaded cost per successfully completed business outcome
Alerting on errors and latency
Evidence the agent stayed inside its authority and control envelope

The result is a governance vacuum. Investment decisions, scaling decisions and risk acceptance are being made on anecdote and demo confidence, without a consistent standard for judging digital workers.

Measurement framework

Three measures of a digital worker.

Every agent Agentometry measures is assessed on the same three dimensions, defined for its specific business function and evidenced from your own telemetry.

A

Efficacy

Does the agent do the business job well?

  • Task success and quality against the defined business outcome, not a benchmark set
  • Reliability and consistency across repeated cases, plus tool-use and decision-trajectory quality
  • Robustness on edge cases, error recovery and behaviour under unfamiliar inputs
B

Efficiency

What does successful work really cost?

  • Model, token and tool spend, plus latency where the process is time-sensitive
  • Human review time, escalations, interventions and rework — the hidden operating cost
  • Throughput against the volume the business actually needs

Headline measure

Total cost per successfully completed business outcome

Fully loaded: compute, tools, human oversight, escalation and rework.

C

Security & control

Does the agent operate within its authority?

  • Observability and auditability of what the agent did, with what data and on whose behalf
  • Permission scope, policy and guardrail violations, and anomalous actions
  • Inappropriate access or use, including human misuse and agent-to-agent misuse

Lifecycle

One performance layer, from development into production.

Development evaluation and production observability are not separate measurement systems. The contract agreed on day one is the same contract the agent is held to in live operation.

01

Define

Specify the business function, desired outcome, performance thresholds, economic target, escalation rules and control envelope. This becomes the Agent Performance Contract.

02

Develop

Test and benchmark the agent against that contract before deployment. Compare prompts, models, tools and architectures, and surface failure modes early.

03

Observe

Apply the same measures to live behaviour and real business outcomes in production. Detect deterioration, drift and changing economics as volumes and inputs shift.

04

Improve

Diagnose root causes, change the agent, validate that the intervention actually improved performance, and decide whether to scale, improve, constrain or stop.

Continuous loop

Improvement feeds back into the contract. Thresholds tighten as the agent matures, and each change is validated against the same evidence base rather than re-argued from scratch.

The core artefact

The Agent Performance Contract.

Before an agent is measured, the business owner and technology team agree what good looks like: the function, the thresholds, the economics and the limits of authority. It is written once and applied everywhere.

  • Signed jointly by the process owner and the engineering team.
  • Benchmarked against the existing human or business-process baseline.
  • Carried unchanged from pre-production testing into live operation.

Agent Performance Contract

Claims Triage Agent · v2.1

In production
Business function
Assess and progress straightforward motor claims
Efficacy target
≥ 97% of claims assessed correctly
Autonomy target
≥ 85% completed without human intervention
Escalation ceiling
< 15% referred to a human handler
Economic target
< £3.00 per successfully completed claim
Human baseline
£14.00 / claim · 18 minutes · 96% accuracy
Control envelope
Defined tool, data and financial permissions; no settlement authority above £2,500
Production threshold
Must remain above agreed limits; breach triggers constrain review within 5 working days

Initial engagement

Start with an Agent Performance Review.

A bounded first engagement covering three to five strategically important agents, typically over four to six weeks. Advisory judgement combined with technical measurement.

4–6

weeks

3–5

agents

  1. 01

    Define the contract

    Agree the business function, thresholds, economics and control envelope with the process owner and engineering team.

  2. 02

    Connect the data

    Ingest existing telemetry from your current stack. No replacement tooling and no re-instrumentation programme.

  3. 03

    Measure actual performance

    Assess efficacy, efficiency and security/control against the contract using live and pre-production evidence.

  4. 04

    Benchmark the baseline

    Compare against the human or existing business-process baseline for accuracy, cost and cycle time.

  5. 05

    Diagnose failure modes

    Identify recurring failure patterns, their business impact and where they originate in the agent's behaviour.

  6. 06

    Recommend the decision

    A clear executive recommendation per agent: Scale, Improve, Constrain or Stop — with the evidence behind it.

The review is deliberately bounded: a defensible view of a handful of agents that matter, delivered fast enough to inform the next investment decision.

Discuss a first review

Cross-platform by design

A layer above your evaluation and observability stack.

Agentometry does not replace your engineering tooling. It sits above it — ingesting the telemetry you already produce and connecting technical agent behaviour to business-process performance, human oversight, economics and control.

Independent. Not built by the platform vendor whose agents are being measured, and not tied to a single cloud.

Additive. No re-instrumentation programme, no migration, no rip-and-replace of existing eval or tracing tools.

Business-connected. Technical traces are joined to outcomes recorded in your case, workflow and finance systems.

LangSmith
Arize
Datadog
OpenTelemetry
Langfuse
Pydantic
AWS
Azure
Google Cloud
Internal logs
Case & workflow systems
Finance systems

Platform names indicate telemetry sources Agentometry is designed to work with. They do not imply partnership, integration certification or endorsement.

Executive scorecard

One page the board can actually act on.

Each score is a decision-support summary, not a verdict. Every number opens onto the underlying evidence: the contract, the sampled cases, the failure modes and the economics behind it.

AgentEfficacyEfficiencyCost / outcomeControlRecommendation

Claims Triage

Motor claims assessment

Above contract on all three measures across 41k claims; escalation trending down.

9188£2.4194Scale

Customer Service

Tier-1 resolution

Cheap and fast, but 1 in 4 resolutions fails quality review on billing enquiries.

7692£0.9483Improve

Procurement

Supplier onboarding

Heavy human review and two out-of-scope data accesses; narrow permissions pending.

8961£18.6072Constrain

Research

Market and competitor briefs

Consistently above analyst baseline on quality with full source attribution.

9584£6.1091Scale

Illustrative figures. Scores are composites of contract-specific measures and are always published with their component detail and sampling method.

Where this goes

Performance management for digital labour.

Within a few years, large enterprises will operate hundreds or thousands of agents alongside their human workforce. That workforce will need what every workforce needs: consistent standards, understood economics, clear accountability and credible governance.

The first engagement measures a handful of agents. The platform that follows gives the enterprise a single, independent view of the whole agent estate — comparable across business units, vendors and clouds, and legible to the board, the regulator and the process owner alike.

Commercially, that means pricing that follows the size and value of the estate under measurement rather than seats or telemetry volume — with value-linked upside where performance improvement can be evidenced.

The estate view

  • 01What agents do we have?
  • 02What business functions are they performing?
  • 03What are their performance contracts?
  • 04How effective are they?
  • 05What is their fully loaded cost per successful outcome?
  • 06How much human oversight do they require?
  • 07Are they operating inside agreed controls?
  • 08Which should we scale, improve, constrain or stop?

Your agents are becoming part of the workforce. Measure them like it matters.

A first Agent Performance Review takes four to six weeks and covers the three to five agents that matter most to your business.

About & contact

Independent by construction.

Agentometry is built by people who have run large operational functions and delivered enterprise technology change. We do not sell agent platforms, so our assessment of an agent’s performance carries no commercial stake in the answer.

Who we usually speak to
CIOs and Chief AI Officers, with the COO or business-process owner as co-sponsor, supported by AI engineering, risk and finance.

Discuss a first review

Tell us a little about your agent estate and we will come back with a proposed scope.

Optional — up to 1500 characters.