You can't optimize what you can't see.
You've rolled out agents internally... but now costs are through the roof and you have no visibility into what they're doing with all those tokens.
It feels chaotic and opaque... because it is.
- When people hit their token limits, there's no way to tell what the spend went toward.
- Requests for additional tokens are not data backed either.
- Spend feels out of control... it keeps going up with no visibility to know where to optimize.
- You don't know where your teams are getting the most value.
- You find out an agent went off the rails when a customer tells you or you run into an incident.
- You're paying for dozens of agents across your fleet to repeat the same work.
- There's no standard path to using or measuring agents.
- Your team feels more productive, but it's really hard to prove it with data.
- You know your agents aren't optimized but there's no data to tell you where to start.
- If your agents were failing or taking anomalous action, you would have no idea.
Your agents are running their own processes.
Agents mean your operations a living system, and you're still managing it like a static one. gjalla is the measurement and feedback loop that unlocks AI-native orgs.
- Measure
- Attribute token spend to the tasks, workflows, and deliverables they produced.
- Analyze
- Find the hotspots of waste, overhead, and opportunities to optimize across your internal agent fleet.
- Optimize
- Mitigate overhead and implement optimization opportunities so your agent fleet is constantly learning.
- Monitor
- Catch anomalies, find and fix emerging issues, and unlock the power of being AI-native.
Why gjalla
Visibility comes first.
Prioritization and optimization are not just numbers, and shouldn't be implemented without your goals in mind. gjalla surfaces data first so you control how your feedback loops work.
Learning across your whole fleet.
The real gains come from agents learning from each other. When one agent figures something out, you shouldn't pay for more to figure out the same thing.
Consistency and control in a world that changes every week.
Models, repos, frameworks, all of them keep changing. What doesn't change is your need to see, measure, and optimize the tools you bring in to your org.
Data privacy is in our DNA.
Our team comes from the worlds of applied cryptography, cybersecurity, and platform engineering. We aren't going for "Big Brother", we're going for the best insights possible while respecting the privacy of your team.
An integrated platform that won't break the bank.
We've built alongside transformative companies. We've seen what works and what doesn't. We bring the best pieces into one platform so your team can get the most out of your AI investments.
Teams already trust gjalla.
“We’ve defined rules and principles that guide our AI through decision-making for our codebase. AI code contributions work toward our long-term goals, not against them.”
“The digests give me confidence I actually know what’s going on and what’s changing. And trust that nothing surprising will pop up.”
“Oh, I had no idea that much of our spend was going toward bug fixes.”
Questions buyers ask
Who is gjalla for?
Companies who've adopted multiple agent vendors across multiple teams and domains; who are transitioning toward AI-native to strive for operational excellence and industry leadership; who have leaders in charge of AI enablement and hundreds or thousands of employees collaborating with AI every day. Your company may not be the right fit today if you have less than 100 employees, implement a single agent vendor, or prefer to build all solutions in-house.
Do you train on our data?
No. Data privacy is in our DNA. Insights are built from derived artifacts, not your raw sessions, and we're happy to accommodate additional security requirements as required by your organization.
How is this different from OpenRouter or LiteLLM?
Unlike OpenRouter or LiteLLM, gjalla is a closed-loop platform that combines monitoring with gateway centralization. This is important because agents are dynamic, not static. A closed-loop self-learning system is imperative for companies that want to achieve AI-native operational excellence.
Do we have to route our traffic through gjalla?
No. Visibility comes first, and it doesn't need anything in the request path: a local scan, a harness plugin, our SDK or OpenTelemetry all work. Applying fixes automatically, like giving each task the right model, works through a gateway: gjalla's, or the one you already run.
What do we show the board?
Where the spend goes by team and by kind of work, and what it produced over time. The right value metrics depend on your business, so we define them with you rather than hand you a generic score.
How is this different from LangSmith, Langfuse or Datadog?
Other tools are optimized for observability of production agents. gjalla is built to bring full visibility, measurement, and optimization to enterprise agent fleets. gjalla's platform is focused on operational excellence within a company, across organizations, and provides the missing piece for truly unlocking AI-native ops. Because it's unified and designed to respect user data privacy, gjalla is also often more cost efficient than other platforms.
How do we get started?
We love to work with customers who are excited about partnering together to build solutions for newly-emerging AI-native operational excellence. Let's chat informally and if we're the right fit, we can move as fast as you need. If you'd like to see numbers first, an engineer can run the free scan of the last 14 days of coding-agent sessions in minutes.
What does it cost?
The scan is free. Fleet and Private deployment plans are custom, priced by the scale of your agent fleet (how many agents and harnesses, and how much session volume) and how you deploy (hosted, or inside your VPC). Details at https://gjalla.io/pricing
Take back control.
gjalla lets you measure and optimize, giving you confidence in the world of agentic enterprise.
Take your company from AI-enabled to AI-native.
How did you find us? What's your most urgent problem?