19%
of AI spend
Private equity firm
Estimated spend traced to personal accounts. Those users are now moving onto corporate accounts.
Value Intelligence
See the work your agents do, and what it returns
Value Intelligence groups every agent session into the business work it served, in your organization's own vocabulary, and ties the spend behind it to the agent, owner and team. It reads from the same record your security team uses for agent risk, so you can weigh what each agent is worth against the risk it carries.
And dozens more
The question has moved from adoption to value
Agents are doing real work across the business, and the board wants to know what that investment returns. Cost Intelligence measures the spend, and Value Intelligence adds the use cases, teams and work it served.
Both read from the record that already powers Geordie's risk intelligence, so the security team that put it in place for agent risk can also bring the business its answer on value.
A use case names the work, whatever tool was used to do it
Every session gets one use case from a catalog built from your own sessions, and a session that doesn't fit is left Unclassified rather than guessed. Knowing what work an agent does also tells security which of its permissions and findings to look at first.
412 agents
25 use cases · 30 days
Product planning and design
$9.8K 8.3%
Infrastructure provisioning and changes
$9.2K 7.8%
Security policy development
$7.8K 6.6%
Code review
$5.1K 4.3%
Marketing content creation
$3.8K 3.2%
Customer issue investigation
$2.5K 2.1%
Product testing and evaluation
$1.5K 1.3%
Competitive intelligence research
$520 0.4%
Workflow automation
$330 0.3%
Personal use
$260 0.2%
412 agents 25 use cases · 30 days
- Product planning and design $9.8K
- Infrastructure provisioning and changes $9.2K
- Security policy development $7.8K
- Code review $5.1K
- Marketing content creation $3.8K
- Customer issue investigation $2.5K
- Product testing and evaluation $1.5K
- Competitive intelligence research $520
- Workflow automation $330
- Personal use $260
Find the waste before it reaches the budget
Value Intelligence finds the patterns that burn spend without producing work and maps each one to the agents, owners and org units behind it. An idle agent that still holds credentials matters to security as much as to finance, because that access can simply be removed.
-
Loops and wasteful token use
Repeated sessions with high token use and very little productive output.
-
Oversized models
Simple tasks running on a frontier model when a smaller one would do the job.
-
Idle agents and provider limits
Agents with no activity for 30 days whose seats, connectors and storage keep costing, and limits that stall work mid-run.
Weigh each agent's risk against what its work is worth
Value Intelligence reads the collection that already powers Risk Intelligence, with no new gateway or deployment. Each risk finding arrives with its owner, team and spend attached, so security can judge an agent doing core engineering work differently from an idle one with the same access.
What early customers found
Graeme Cantu-Park, CIO and CISO at Matillion
$7K
a week
Professional services
Caught in a single looping chat, while role-level usage showed which teams to support next with enablement.
“The conversation has changed from getting everyone to use AI to what value we are actually getting from it. We could tell departments how much they were spending, but not the use cases behind it. Geordie has given us visibility into those use cases on a department, organization or even individual basis, and tied the cost back to those core pieces of work.”
“I used to rely on people telling me their two-hour AI saves each week to feed my ROI formula, and I knew I was probably missing half of it. Now Geordie is a validation point for cost, agent runs and what teams are actually working on, and I can apply that to our full value and ROI models.”
See what your agent spend is delivering
Connect Geordie to the agents your teams already run, and find out which work earns its cost back and which risks are worth carrying for it.
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Related resources
Blog Cost & Value
Value Intelligence: Connecting agent spend to security, the work, and value it returns
What do agents cost and deliver? Spend tied to the work agents perform, the value it returns and the risk security teams manage.
Blog Discovery & Posture
Shelved agents and the case for agentic lifecycle management
When enterprises iterate on their agent workflows, older agents rarely get decommissioned.
Deep Dive Cost & Value
Understanding the cost, the output, and the ownership gap across your agentic workforce
What 50+ organizations running agents in production told us about agent spend, who owns it, why the bill doesn't explain itself, and what to do instead of freezing.
Cost Intelligence measures what agents spend, down to the agent, model and owner. Value Intelligence adds the organizational context behind that spend, meaning the use cases, teams and work it served, so you can judge what the spend delivered as well as how large it was. Cost Intelligence remains part of it.
From your own sessions. Geordie describes sessions over 30 days, proposes a catalog of 12 to 40 use cases once 500 have a description, checks it for naming, overlap and coverage, and then fixes it so months compare like with like.
It reads the user's own turns, the tools the agent called and the model it used. Descriptions never name people, companies, tickets, repositories or file paths. Both steps run through AWS Bedrock in Geordie's own AWS account, and nothing is sent to consumer products or used for training.
Every label traces back to the description it was made from, which you can read in the activity view. The confidence score is the model's own estimate of fit rather than a measured accuracy, and when confidence is low the session is marked Unclassified instead of guessed.
No. Value Intelligence reads the same collection that powers Risk Intelligence, across endpoint, cloud and SaaS, code and browser, with no gateway in the path.
Only sessions with usable user text are described, so a chat deleted before capture counts as Insufficient content. Because descriptions are short and anonymized, two projects doing the same kind of work share a use case.