Delivered · published
An agent workspace where AI agents do everyday business work
A proprietary agentic platform that gives AI agents company context, structured work, recurring schedules, connected tools and deployable sub-applications inside one operating environment.
- Client
- AngajatAI
- Industry
- Company knowledge and internal operations
- Loop
- The numbers
- What we built
- AI agent workspace + graph memory + governed execution
- Status
- Delivered · published
The challenge
What was getting in the way
Teams want AI to work with their documents and tools, not require a fresh explanation for every task. They also need to know what it is doing, what is blocked and what needs approval.
Business information, procedures and recurring work are usually spread across documents, inboxes, project tools and internal software. AngajatAI brings those sources into one operating environment where a digital employee can understand company context, take responsibility for work and use approved tools.
A standalone chat can answer a question, but it does not provide a durable operating model for business work. Agents need persistent knowledge, task ownership, schedules, system access, review states and focused interfaces. Without those layers, people must rebuild context for every request and cannot reliably see what an agent is doing, what is blocked or what requires approval.
- Documents and procedures are connected to a graph memory that exposes relationships across company knowledge.
- Requests become managed tasks with ownership, progress, blocker and review states for both agents and people.
- Recurring work is defined as scheduled jobs and remains visible in a shared operational calendar.
- Approved integrations and generated sub-applications extend what agents can read, prepare and execute from the same workspace.
Approach
How the system works
We built a workspace where AI agents use company knowledge, carry out assigned tasks and run scheduled work through approved tools. Permissions, progress and human review remain visible.
- 01
Agent workspace
A shared dashboard combines conversation, document search, task planning and direct access to company applications.
- 02
Graph memory
Documents, procedures and business facts form a connected knowledge layer that agents can retrieve from before answering or acting.
- 03
Execution layer
Tasks, recurring jobs, integrations and deployable sub-apps turn agent reasoning into visible, controlled operational work.
Agents work while the team sees progress
Rules handle
- Maintain stable task identifiers, ownership, status transitions and review states.
- Trigger recurring jobs from approved schedules and record each run outcome.
- Enforce permissions for knowledge sources, integrations, actions and generated applications.
- Move structured data through direct connectors and controlled application interactions.
- Record retries, failures, blockers and consequential state changes for audit.
- Manage the deployment and lifecycle state of applications created inside the platform.
AI handles
- Retrieve relevant company context from approved documents and graph memory.
- Break requests into tasks, select the next workable issue and update progress as evidence changes.
- Use connected tools within the authority assigned to the agent and escalate exceptions outside that authority.
- Generate focused sub-application drafts from an approved business requirement and connect them to the workspace.
- Explain what was completed, what remains uncertain and which decision needs a person.
People decide
- Approve the documents, procedures and data sources that become company memory.
- Set integration permissions and decide which actions an agent may execute without confirmation.
- Review blocked, ambiguous or high-impact tasks before business state changes.
- Approve generated applications, production deployment and any expansion of agent authority.
The website
The published web experience
Explore selected screens from the project. The complete site opens separately for current content and full interaction.
Operate from one agent workspace
The dashboard gives people one place to talk to their digital employee, search company documents, plan work and start purpose-built applications. Agents share the same operating environment instead of living in separate chat windows.
Captured from the published website.Stack
Built with
Every tool the system connects, and the job it does.
Company knowledge
Approved documents, procedures and business information used by the graph memory and agent retrieval layer.
Task and job operations
Persistent work queues, review states and recurring schedules shared by agents and people.
Connected applications
Direct API integrations plus controlled interaction with tools that do not provide a public API.
Workspace applications
Generated and deployed sub-apps that provide purpose-built software while remaining connected to agents and company context.
Limits
Limits of this case
- Agent output depends on the quality, freshness and permission scope of the knowledge available to it.
- Controlled interaction with third-party interfaces may need maintenance when those interfaces change.
- Generated applications still require security review, business ownership and release approval before production use.
- Recurring jobs require monitoring and exception handling when a dependency or external service is unavailable.
- The case-study frames are dated captures. The live product remains the source for current behaviour and access conditions.
Possible next phase
Expand the platform one operational area at a time, measure completion, review and rework, then grant broader agent authority only where the evidence supports it.
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