Public software company
Setting up was seamless and I love the experience.
Solutions
We deploy the agents with you. Then we prove they work.
Agents are easy to demo and hard to trust at scale. We work alongside your team to put autonomous agents into your stack, and build the evals that tell you whether a workflow is good enough to widen.
What's slowing you down
A demo is not a rollout
One impressive run tells you nothing about the next hundred. Without measurement, expanding agent coverage is a matter of opinion, and opinion does not survive an incident.
Security review stops most pilots
Where does the code run, who holds the tokens, and what did the agent touch. If the answers are not structural, the pilot stays a pilot.
Nobody can say whether it is improving
Teams change prompts, models, and tools with no baseline. Evals turn "it feels better" into a number you can take to a review.
How a deployment actually goes
We pick one workflow with you
Something with a clear pass condition and real value, usually PR verification or nightly regression. Narrow enough to judge, useful enough to matter.
We deploy it in your environment
Agent computers run in your VPC under BYOC when that is the requirement, with gateway policy scoped to the systems that workflow needs and nothing else.
We build the evals with your team
A graded set of runs that reflects your codebase, so you can compare models, prompts, and harnesses on your work rather than a public benchmark.
You get a baseline and a trend
Every change is measured against the same set. When someone asks whether the agents are getting better, the answer is a chart.
You widen team by team
Gateway profiles let you extend access one group at a time, so a rollout is a sequence of small decisions instead of one large one.
How Islo maps to it
Deployment
We do it with you, not at you
Our team works alongside yours through the first workflow, so the knowledge stays in-house instead of leaving with a consultant.
Evals
Trust you can measure
Graded runs on your own codebase, in isolated computers, so model and prompt changes are compared on evidence.
BYOC
Your cloud, your policies
Agent computers run in your VPC. Code and data stay in accounts you control and audit the way you already do.
Audit
Per-request trails, exported
Every outbound call an agent makes is logged and streamed to your SIEM, so review is a query rather than a meeting.
Rollout
Least privilege per team
Scope credentials and network access per team and per workflow, and expand only where the evidence supports it.
Where teams start
Teams running agents on Islo
Common questions
What does "deploy together" actually mean?
Our team works with yours to get the first workflow running in your environment: choosing it, wiring the gateway policies, and building the eval set that grades it. You end up owning it, not depending on us to run it.
Why do evals matter this much?
Because without them, expanding agent coverage is guesswork. A graded set on your own codebase lets you compare models, prompts, and harnesses, and gives you a number to show a review board.
Can everything run inside our own cloud?
Yes. BYOC deploys the Islo control plane and agent computers inside your cloud account. Scheduling, gateway policies, and audit stay within your network boundaries, with logs exported to the sink you already use. Code and data do not leave your accounts.
How do we satisfy a security review?
Isolation per run, credentials injected at egress so tokens never reach the model context, egress rules per computer, and a per-request audit trail. These are properties of the platform, not settings you have to remember to turn on.
Which harnesses and models are supported?
Islo is harness-agnostic. Claude Code, Codex, and Cursor run natively, and custom harnesses run on the same infrastructure, which is what makes comparing them on evals meaningful.