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. You can see which work earns its cost back and where budget is going to waste.
And dozens more
The question has moved from adoption to value
Most organizations now have agents doing real work across engineering, operations and the business, and the board wants to know what that investment is returning. Part of the answer is spend, which Cost Intelligence measures down to the agent, model and owner. The rest is organizational context: the use cases, teams and work that the spend actually served.
Value Intelligence brings both together on the same understanding of every agent that already powers Geordie's risk intelligence, so the record that tells you what an agent did also tells you what that work was for and what it cost.
A use case names the work, whatever tool was used to do it
Every session gets exactly one use case from a catalog built from your own sessions, so the categories read in your vocabulary. Each label traces back to a short description of the work, and a session that doesn't fit is left Unclassified rather than guessed.
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 watches for the patterns that burn spend without producing work, and maps each one to the agents, owners and org units behind it, so the finding lands with someone who can act on it.
-
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.
Two sides of the same coin: Risk and Value Intelligence from the same record
Value Intelligence needs no new gateway or separate deployment, because it reads the collection that already powers Risk Intelligence. This brings AI Ops, security, and finance teams onto the same page, reading off a single data source to answer their own questions.
What early customers found
$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.
Graeme Cantu-Park
CISO and CIO @ Matillion
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 where budget is going to waste.
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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.