Outcome-driven agent creation
Start from a job to be done, then review the proposed instructions, interaction style, supervision, tools, and tests.
All products
Agent platformBlazorly Agent
Build and deploy agents
Build, test, deploy, and govern agents from one studio.
Define the outcome, choose what the agent can use, connect approved knowledge and applications, test its behaviour, and publish a controlled version to the channels where work happens.
Desired outcome
Prepare an evidence-backed weekly revenue brief.
Gather approved account context, flag uncertainty, and ask before any external action.
Supervision Supervised
Knowledge 8 sources
Connections 2 grants
Evaluations 12 passed
Draft readiness checks passed Publish draft
Where it fits
The execution and lifecycle platform behind standalone agents and Crew Mates.
Private betaCore capabilities
What Agent is designed to do.
Each capability below is tied to a real product surface in the current Blazorly codebase.
Tools and isolated workspaces
Enable web research, files, code execution, long-running sessions, memory, subagents, and other capabilities as the outcome requires.
Knowledge, skills, and memory
Give each agent durable context and reusable guidance while keeping its purpose and boundaries visible.
Connected applications
Grant access to selected external accounts and actions through explicit connector permissions and receipts.
Test and evaluate before release
Use a test workspace, repeatable evaluation cases, traces, and draft-versus-live comparisons before publishing.
Deploy and observe
Publish versioned agents, expose approved channels or APIs, schedule work, and review runs, approvals, usage, and failures.
How it works
A clear path from intent to controlled work.
- 1
Define the outcome
Describe the job, target users, success conditions, and the level of supervision required.
- 2
Configure capabilities
Add only the tools, knowledge, skills, models, and connected accounts needed for that job.
- 3
Test with evidence
Run live conversations and repeatable evaluation cases against a pinned draft revision.
- 4
Publish and operate
Release a controlled version, then monitor runs, approvals, schedules, channels, and activity.
Suitable use cases
Where Agent earns its place.
Example patterns only. The exact setup depends on the workflow, product configuration, permissions, and beta availability.
Research and decision support
Gather current evidence, compare sources, use internal knowledge, and produce a bounded brief.
Inbox and operations assistance
Classify requests, draft responses, maintain context, and pause before sensitive external actions.
Long-running technical work
Use isolated files, commands, execution sessions, and goal tracking for sustained project-shaped tasks.
Product boundary
Capability is explicit, and deployment is versioned
An agent can only use the tools, knowledge, connections, and release settings made available to it. Exact provider, connector, channel, and action availability depends on workspace configuration and the supervision policy applied to the agent.
Private invitation beta
Bring the work you want to change.
Tell us whether you need an operational application, a focused AI agent, or a supervised Crew around a product.