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Technical platform

Build agents that fit your business.

For the people who know the process and the people who configure the technology. Define the agent’s job, equip it with expertise and tools, set its boundaries and inspect its work.

01 · Architecture

Your organization is the starting point.

Departments, teams and roles connect the people responsible for work with the agents that help carry it out.

Organization

Departments, teams, people and reporting lines

Authority

Role responsibilities, information access, operating limits and human review

Work

Role agents plan and delegate; specialists carry out defined tasks

Connections

Assigned tools, knowledge, databases and external services

Architecture overview. The organization defines responsibility; applications provide capabilities for the work.

A role with an owner

A role retains its place in the organization when its occupant changes. Its delegate agent works within the assigned responsibilities and authority.

Specialists for the task

Role agents can call specialists for focused work. Giving a task to another agent does not grant it a larger operating allowance.

Boundaries across teams

Reporting lines and information clearance answer different questions. Cross-team bridges define permitted collaboration between roles.

Supporting files can also be associated with a workspace’s tasks. See an authorised colleague retrieve a receiving record →

02 · Shared expertise and agent building

Your expertise. Your tools. A specialist built for the job.

A specialist does a focused job. Its Harness brings together instructions, information, tools and operating rules. Configure the parts that matter for the task, then inspect a real run. A pipeline connects the stages when the work needs more than a direct answer.

Decide how your agent works.

Job and expertise
Write the agent’s purpose, procedure and expected output. Assign reusable Context and preview how the instructions fit together. See the builder walkthrough →
Model and execution
Choose a supported model and runtime; configure execution, memory and routing settings for your deployment. Tool support and controls vary by runtime. Inspect the configuration options →
Knowledge and tools
Set the information the agent may retrieve and the operations it may call. Connections and permission to use them need their own setup. See a connected tool in use →
Limits and authority
Establish the responsible role, trust and operating boundaries. Instructions describe the task; they do not replace permission checks. Explore operating controls →
Testing and evidence
Compare a representative input with the actual output. Inspect the included instructions and any tool calls; a configuration preview makes no model call. Watch a test, instruction change and retest →
Reuse and coordination
Select a shared specialist within the allowed scope. Use it directly, connect it in a pipeline, or configure coordination with other agents. Explore agent-to-agent coordination →

See two colleagues produce and review a handover →

The demonstrated workflow runs in sequence. Its generated Markdown is manually saved to Knowledge before review; the pipeline does not export or approve it automatically.

Configuration screens and technical authoring

The execution editor exposes Runtime, Model, Execution, Constraints, Memory, Instructions, Context, Tools, Routing and Trust. Start with the job and required controls; choose additional settings when the task needs them.

The instructions editor separates expertise, procedures, references and constraints. Reusable Context is assigned separately. Knowledge eligibility is not proof of retrieval, and a saved model or routing choice is not proof that the provider is configured or a run succeeded.

Use the product’s configuration screens, or integrate through the supported APIs and SDK paths. The deployment must supply the required model access, integrations and permissions. A saved draft or registered gateway does not establish a working deployment.

Inspect APIs and SDK integration → · Inspect the connected test and instruction change →

Inside the Harness: instructions, information and controls
the current Harness overview
Actual configuration screen from the fictional Northstar demonstration. The cards organise setup; their presence does not prove every component ran.
What each Harness component contributes
In the productWhat it means
IntentThe role’s job description: what its agent is there to do.
Context (skills)Reusable instructions assigned to an agent, such as the handover format. The run still checks whether they can be included.
KnowledgeInformation the agent may retrieve when eligible. Permission to retrieve is different from information actually used.
DirectivesStanding instructions for roles or units.
Enforcements (hooks)Operating limits and allowlists. This is the operating-envelope configuration, not a general scriptable-hook library.
Loops (commands)The current page supports reviewing proposed improvements to Context. It does not demonstrate a general command library or scheduled learning.
ToolsCallable capabilities, separate from reference information. Configure the connection and the agent’s permitted use.
What an agent getsA diagnostic of the composed configuration. It stops before a model call; inspect a real run to check what was used.
Publication, access and copying

A role can publish to its own unit or an ancestor. Consumption through that placement is limited to the selected unit; publication does not automatically spread access through the organisation or grant execution authority. Existing assets without a unit target use a separate organisation-level path, still subject to access checks.

Assigning Context saves a reference to the instructions, rather than making a private copy. In the handover demonstration, Daniel authors the specialist and Avery selects the same saved Agent. Both have organisation-wide build administration, and role/trust preparation was explicit. It does not establish that every employee can discover or run the specialist.

Duplicating a pipeline creates another graph. It does not copy a complete Harness or grant additional permissions. Configuration history restores its supported saved fields; it does not undo completed work or restore an entire pipeline graph.

Shared setup and access to business information are separate. Check the intended roles, data access and execution permissions in your evaluation.

Inspect the pipeline and available starting points
the saved handover pipeline
The demonstrated graph connects supplied input, the handover specialist and output. The matching executions record the assigned Context as included.

The two completed runs use the same specialist and assigned four-heading format. They demonstrate sequential execution, not parallel branches, retries or updates to operational records.

Six generic starter configurations are defined: Basic Q&A Assistant, Conversational Tutor, Research Specialist, Code Developer, Code Reviewer and Data Analyst. They still need model, permission and task-specific setup. The Northstar handover is a demonstration configuration, not a ready-to-run business application included in every installation.

Inspect the actual outputs and saved document →

Earlier instruction, workflow and restoration demonstrations
Silent demo · captions includedA later answer uses the saved instructions · 31 seconds
A later saved answer uses the required headings without being reminded. Payment proof is still missing.
Read the transcript

Save invoice-review headings, assign them to the assistant and check the setup.

The assignment preview checks setup. The saved answer is a separate actual response.

This is a saved-record presentation of instruction use, not a new model run during preview, payment approval or model retraining.

Fictional demonstration. Edited recording; saved-record views are labelled.

  1. 00:00:00.000 — Save steps for the invoice assistant.
  2. 00:00:07.000 — Check that the assistant receives them.
  3. 00:00:11.680 — This is a preview, not a new answer.
  4. 00:00:16.000 — The next answer uses the saved headings.
  5. 00:00:20.103 — Saved response shown on a review page.
  6. 00:00:24.000 — The request did not name those headings.
  7. 00:00:27.415 — No payment proof means the answer says so.

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Earlier instruction setup · recording download

Initial setup. The earlier example saves invoice-review instructions, previews the assignment and saves a plan. See the creation and setup steps. This is preparation, not a completed run.

Set up an assistant for invoice review · 30 seconds
Save reusable instructions and limits, preview the instructions the assistant will receive, and place the assistant into a saved sequence of planned steps. This short edit shows setup; it does not run those steps.

Download the original recording or read its transcript

Save reusable instructions and limits, preview the instructions the assistant will receive, and place the assistant into a saved sequence of planned steps. This short edit shows setup; it does not run those steps.

  1. 00:00:00 — Save instructions and clear limits that can be reused for invoice review.
  2. 00:00:10 — Preview the instructions sent to AI. This preview does not run the AI.
  3. 00:00:16 — Create an AI assistant with a clear invoice-review purpose.
  4. 00:00:22 — Save the assistant in a plan. This clip does not run the plan.

Download captions (VTT)

Download the original recording (embedded English remains).

Inspect workflow building and configuration history

The new walkthrough follows a saved three-step sequence through its completed result. The five-node invoice example below separates the earlier setup from a new test that stops because the agent has no trust chain.

Silent demo · captions includedRun a saved three-step handover workflow · 48 seconds
All three steps complete and the saved answer summarizes the supplied dock facts.
Read the transcript

Supply dock details and the person handling follow-up to the saved input → summary → output workflow.

The completed run record supports the result. No separate human review is shown.

No tool is called and no operating record changes. An answer summarizing a status does not perform the underlying operation.

Fictional demonstration. Screenshot walkthrough; saved-record views are labelled.

  1. 00:00:00.000 — Open the saved workflow. It has three connected steps.
  2. 00:00:05.786 — It takes information, summarizes it and returns an answer.
  3. 00:00:12.000 — Supply the dock details and the person handling follow-up.
  4. 00:00:17.949 — The request asks for a short summary and no record changes.
  5. 00:00:24.000 — Run the saved workflow. All three steps complete.
  6. 00:00:30.062 — The saved answer uses the supplied dock details.
  7. 00:00:36.000 — This is a summary of supplied facts.
  8. 00:00:40.854 — No tool is called and no operating record is changed.

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Earlier workflow setup and a refused test
Silent demo · captions includedA new pipeline test stops without an authority chain · 50 seconds
The first agent refuses with “No trust chain established for this agent.” The new execution is failed and produces no invoice decision.

A later test without an authority chain returns “No trust chain established for this agent.” Earlier setup scenes are labelled separately. The test uses reconstructed example line items; it does not extract a new invoice or produce an invoice decision.

Read the transcript

A later test recreates the earlier five-node invoice-review scenario using a template with explicitly reconstructed line items.

No authority is added. The film separates the new refusal from the original setup.

Reconstructed line items are not freshly extracted evidence, and the stopped test produces no invoice decision.

Fictional demonstration. Edited recording; saved-record views are labelled.

  1. 00:00:00.000 — A new test stops: “No trust chain established for this agent.”
  2. 00:00:04.960 — Without an authority chain, the pipeline does not proceed.
  3. 00:00:10.000 — Earlier setup: the invoice specialist is configured.
  4. 00:00:14.961 — This is the original scenario, not the newly created test record.
  5. 00:00:20.000 — The earlier setup asks which capabilities the specialist needs.
  6. 00:00:25.040 — This configuration screen does not grant authority to execute.
  7. 00:00:30.000 — The original graph supplies the five-node scenario for the new test.
  8. 00:00:35.271 — The new test reuses a template with reconstructed line items.
  9. 00:00:40.000 — The new test’s first agent returns the missing-trust-chain refusal.
  10. 00:00:45.276 — No authority was added and no invoice decision was produced.

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Compare and restore configuration

Save configuration versions, inspect field changes and restore a prior version. Pipeline configuration history covers its name, description, pattern and status; it does not restore graph nodes, connections or actions already taken in external systems.

Silent demo · captions includedRestore an earlier set of assistant settings · 31 seconds
The earlier wording is restored, and all 15 recorded settings match.
Read the transcript

Compare two saved versions after changing only the assistant description.

Saved comparison records and the native wording support the narrow restore result.

This restores assistant settings, not a whole workspace, pipeline or all work.

Fictional demonstration. Edited recording; saved-record views are labelled.

  1. 00:00:00.000 — Compare two saved sets of settings.
  2. 00:00:03.403 — Saved results; this is a review page.
  3. 00:00:07.000 — Only the description was changed. Both versions were saved first.
  4. 00:00:14.000 — Bring back the earlier version. All 15 saved settings match.
  5. 00:00:23.000 — The app shows the earlier wording again.
  6. 00:00:27.156 — This restores settings, not all work.

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Model and runtime choices

Provider options include OpenAI, Anthropic, Google, Azure and Ollama, subject to deployment configuration. Tool support, memory settings and enforcement differ by execution runtime. Evaluate the provider and runtime together against the tools and controls your workflow needs.

Discuss your agents, integrations and access requirements →

03 · Agent-to-agent coordination

Put the right agents on the same job.

Bring contributions from different teams into one answer. In the staffing example, Finance checks the figures and Operations checks the workload.

This recording shows agents working together inside Aegis. External A2A compatibility needs a separate evaluation of the other system and its supported protocol.

See the coordinated-work demonstration →

Scope: this section demonstrates coordination between Aegis agents. The external-agent service invokes REST endpoints; an A2A registration does not establish an external Agent2Agent protocol call.

  1. Discover capabilities. Find configured Aegis agents suited to the task.
  2. Choose coordination. Route to a specialist, assign a supervisor or combine contributions from several workers.
  3. Set the work and limits. Define the objective, participants and relevant authority.
  4. Inspect the outcome. Review returned work, exceptions and completion before accepting the result.
Recorded configuration of manager and worker agents. This capture does not show a completed multi-agent run.
Watch two teams answer a planning question · 72 seconds
Silent demo · captions includedFinance and Operations prepare a staffing draft · 72 seconds
Two worker tasks finish. A separate correction request produces a combined draft with the corrected 14.3% calculation.
Read the transcript

Avery asks Finance and Operations to examine supplied fictional staffing and cost figures.

The first percentage error, explicit correction request and resulting internal draft remain visible.

This is calculated from supplied figures, not measured savings. It shows neither spending nor human approval. One operator uses separate demonstration accounts.

Fictional demonstration. Edited recording; saved-record views are labelled.

  1. 00:00:00.000 — Avery, the company lead, asks Finance and Operations to help.
  2. 00:00:02.905 — Fictional staffing facts; separate accounts used by one operator.
  3. 00:00:06.000 — Both sides recorded permission to work.
  4. 00:00:11.132 — Saved records shown on a review page.
  5. 00:00:16.000 — The Operations assistant checks the plan.
  6. 00:00:23.000 — The Finance assistant checks the costs. These are the two helpers used.
  7. 00:00:31.000 — The first answer is saved for review. Its percentage needs a correction.
  8. 00:00:37.000 — A separate request asks for a correction.
  9. 00:00:40.727 — The original answer stays unchanged.
  10. 00:00:44.000 — The Finance assistant returns its checks.
  11. 00:00:50.000 — The Operations assistant returns its work. Both tasks finish.
  12. 00:00:56.000 — The combined answer corrects the calculation to 14.3%.
  13. 00:01:00.119 — This is a calculation on supplied figures, not measured savings.
  14. 00:01:05.000 — The corrected answer is saved as an internal draft.
  15. 00:01:08.051 — Two worker tasks finished; no spending or human approval is shown.

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Internal coordination and external A2A support

Aegis’s A2A workspace provides internal discovery, routing and orchestration. Available patterns include router, supervisor, blackboard and ensemble. Internal coordination is distinct from interoperating with an outside agent server.

The external-agent service currently invokes REST endpoints. Selecting A2A or MCP in its registration does not make those protocols invokable on that service. External MCP tool connections use the separate MCP integration described below.

The Agent2Agent protocol defines communication between independent agents. Its general capabilities are not a claim of complete Aegis protocol compatibility.

04 · Model Context Protocol

Connect tools to agents, and Aegis to other clients.

Let an agent use a connected tool, or make selected Aegis functions available to another application. The three paths below have different setup and access requirements.

Tools built into Aegis

One enterprise MCP server provides tools for planning, routing, knowledge lookup, escalation, delegation and submitting results to the Claude runtime.

External tools for agents

Register a server, discover its tools and attach the capabilities an agent needs. Connection and execution support depend on the transport and runtime.

Aegis tools for other clients

Other applications can call selected Aegis functions through MCP. This must be explicitly enabled, and each operation needs authorization.

Silent demo · captions includedApprove a public read and inspect its final answer · 80 seconds
The approved public read returns ten category names. The final answer confirms that the read was completed.

Avery makes two decisions before the read: the agent escalation, then the tool approval. The final answer confirms completion; its optional follow-up question concerns new work. This is one observed public read, not a general reliability claim.

Read the transcript

Maya uses the existing Platform Services assistant and assigned public get_categories tool with the unchanged earlier test request.

Avery approves the agent escalation, then separately approves the tool-gate hold. Both decisions precede the read.

This is one observation, not a general reliability claim. It is an unauthenticated public read with no outside writes, using separate fictional accounts operated by one operator. Optional follow-up confirmation in the final answer concerns new work.

Fictional demonstration. Screenshot walkthrough; saved-record views are labelled.

  1. 00:00:00.000 — The actual answer says the public read was approved and executed.
  2. 00:00:08.254 — Its final confirmation concerns optional follow-up work only.
  3. 00:00:16.000 — Maya uses the existing Platform Services assistant and public tool.
  4. 00:00:21.877 — The request is unchanged from the earlier test.
  5. 00:00:26.000 — Avery, the company lead, approves the agent’s escalated request.
  6. 00:00:33.877 — The decision is saved against that exact request.
  7. 00:00:42.000 — The tool gate separately holds the call; Avery approves it.
  8. 00:00:49.080 — Two recorded decisions precede this read.
  9. 00:00:54.000 — The actual public tool returns ten category names.
  10. 00:00:58.464 — This shows an unauthenticated read; no outside records change.
  11. 00:01:04.000 — The unchanged answer consistently reports the completed read.
  12. 00:01:11.685 — One observation, not a general reliability claim.

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Configure an external MCP server
  1. Open Tools → MCP Servers . Enter the name, endpoint, transport and enabled state.
  2. Configure the supported credential method. A secret URL can be referenced as env:YOUR_MCP_URL ; the environment variable holds the complete connection URL.
  3. Save and inspect discovery. HTTP/SSE discovery runs initialization and requests the tool list.
  4. Attach the server or a discovered tool to an agent, using its agent identifier and the tool name where applicable.
  5. Run a task that needs the tool and inspect the actual result and permissions. Registration alone proves no business operation.

Compatibility to check: registry discovery supports HTTP/SSE. Its discovery client does not forward Authorization headers, so bearer-token or OAuth support must be verified on the chosen execution path. Stdio needs a supported runtime and operator allowlists; a stored WebSocket entry is not proof of execution support. Private-network endpoints need deployment review.

The walkthrough shows one completed individual-tool call through an external HTTP server.

The individual-tool invocation path checks the tool binding and requires approval. The Claude adapter registers the whole server, so tool exposure and approval behavior must be checked for that runtime.

Built-in enterprise tool inventory

The enterprise server exposes ten tools. These names describe tools, not ten separately installed servers.

Plan and route
decompose_objective , route_task
Delegate and escalate
delegate_to_agent , escalate , invoke_task_agent
Knowledge and connected systems
query_knowledge , check_directive , execute_connector_query
Return the work
create_deliverable , submit_upstream

Connector queries can also write through supported API connections; review the agent’s assigned source and permitted operation.

MCP means Model Context Protocol: a common way to expose tools and information to AI applications. Read the protocol overview .

Enable Aegis tools for an external MCP client

Inbound MCP admission is closed by default. An operator must explicitly enable it and configure the allowed origins. Clients without an Origin header need an explicit admission choice.

Transport admission is separate from authorisation. Verify the caller’s identity, organisation and permission for each operation you intend to expose. Test the actual external client and deployed configuration before allowing business work.

This describes the configuration path. The public external-tool recording shows Aegis calling an outside server; it is not evidence of a client calling into Aegis.

Choose the connection your task needs.

Start with the path your application needs. Compare its connection, credentials and review behavior here, then inspect the detailed setup and recorded proof. Confirm the runtime and version used in your deployment.

Runtime and connection choices
PathConnection and credentialsAuthority and reviewEvidence and next check
Built-in tools · Claude Agent SDKOne embedded MCP server provides ten enterprise tools. Uses the agent’s execution identity; configure connected-system credentials separately.Tool-specific authority and information-access checks apply. The inventory is not a grant to every business record.Inspect the inventory. Confirm the deployed runtime, required tool and permitted operation.
External MCP · Claude Agent SDKHTTP/SSE with configured headers or a URL secret reference. Stdio requires an operator-allowed command and environment setup. Discovery uses HTTP/SSE without forwarding Authorization headers.SDK registration exposes the server’s tools; do not assume a selected tool is an exclusive grant. Runtime governance and per-call review still apply.See the separate public-read example. It does not prove authenticated access on this SDK path. Test credentials, tool scope and approval in your deployment.
External MCP · native tool invocationThe native invoke_mcp_tool path calls HTTP/SSE. Uses a URL or URL secret reference; its transport does not forward configured Authorization headers. No stdio or WebSocket invocation here.An individual tool binding is enforced; an unbound entry grants the server scope. The tool approval gate runs before the call.Public-read recording: two decisions, ten returned categories. Test your service, credentials and any write separately.
External client → Aegis MCPInbound SSE through enabled Aegis service endpoints. Configure allowed origins and, for clients without an Origin header, explicit admission.Admission is closed by default. Transport admission does not establish caller identity, organisation access or operation permission.Inspect inbound setup. No inbound-client film is supplied. Verify authentication and the exact exposed operation before business use.
Aegis agents → other Aegis agentsInternal discovery and orchestration use configured participants and Aegis execution identities. This is distinct from calling an outside agent.Role authority and delegation boundaries apply; configure who can contribute and who reviews.Finance and Operations contribute to one answer. Check participant access, failures and review requirements for your workflow.
Aegis → external agent or serviceThe external-agent service invokes REST endpoints with configured authentication. It accepts A2A/MCP registrations, but does not invoke those transports.Invocation includes authority, rate and budget checks. Endpoint credentials do not replace Aegis permissions.Inspect external-agent support. Configuration is described below; no invocation of this service is shown. Test the intended endpoint, authentication, permissions and failure handling.

Also check knowledge access and operating oversight. Shared instructions do not grant business-data access. The HR handover uses supplied facts, not retrieved HR records.

05 · Systems and APIs

Work with the systems you already use.

Read information from a connected system and use it in an answer. The example below follows an approved public-data read.

Connection paths to evaluate for your workflow
Connection Current capability Check during evaluation
Databases PostgreSQL, MongoDB and Redis query paths Assigned connection, permitted queries and network access
Business APIs REST and GraphQL requests Authentication, method, payload and read/write permissions
External agents or services REST invocation with authentication, rate and budget checks Actual response, failure handling and permitted operations
Your application → Aegis REST API and Python SDK operations Identity, organization scope and operation permissions
Notifications Delivery adapters for Teams, Slack, Discord, Telegram and Notion Channel configuration and which events actually trigger delivery

Assign a connection to the agent that needs it.

The connector tool resolves an assigned connection alias within the agent’s organization. Agree the data to read, the operations permitted and the expected result, then test the complete path.

The earlier screenshot shows a successful REST connection test. The walkthrough below follows a later approved read into the agent’s answer.

Earlier connection test in the fictional demo environment. The walkthrough below separately demonstrates agent use.
Silent demo · captions includedUse one approved public task read · 34 seconds
The connected source reports that task 1 is unfinished. The answer uses that status.
Read the transcript

The Accounts Payable assistant requests one public example task from an outside source.

Avery approves the requested read before the result returns.

No company data is used and no outside records change. This cut ends before the separate reverse-direction REST example.

Fictional demonstration. Screenshot walkthrough; saved-record views are labelled.

  1. 00:00:00.000 — The Accounts Payable assistant requests one outside read.
  2. 00:00:04.653 — The source contains public example tasks.
  3. 00:00:08.000 — Avery approves the requested read.
  4. 00:00:10.957 — The app records that decision before returning the result.
  5. 00:00:16.000 — The outside source says task 1 is unfinished.
  6. 00:00:20.309 — The assistant explains: the task is not finished.
  7. 00:00:25.000 — This proves one permitted read and use of the returned data.
  8. 00:00:29.655 — No company data is used. No outside records are changed.

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Connection coverage and developer example
Silent demo · captions includedA separate program reads assistant metadata · 15 seconds
The saved REST response returns the named assistant and its status.
Read the transcript

A separate program requests one saved assistant’s metadata from Aegis.

This shows a read response; no approval or new agent execution is shown.

This is a labelled saved-record view, not a native external application capture.

Fictional demonstration. Edited recording; saved-record views are labelled.

  1. 00:00:00.000 — A separate program reads one assistant.
  2. 00:00:03.640 — Saved result; this is a review page.
  3. 00:00:07.000 — The request returns the named assistant. It only reads information.

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The request behind the external read

The recorded Python client made this request through the REST API. Replace the placeholder with an agent your account may read; provide the sign-in token through the program’s environment.

GET /api/v1/agents/{agent_id}/summary
Accept: application/json
Authorization: Bearer <token from environment>

The saved response returned HTTP 200, the requested agent identifier, the name Accounts Payable Lead Agent and status active. These are saved agent details, not a task result.

The account needs permission to read agents in that organization. An appropriately scoped API key is another supported sign-in method, but the recorded example used the owner’s sign-in token. Missing access, a failed request or an unexpected agent identifier must be treated as a failed read.

MySQL and SQLite connection tests do not establish query execution. SOAP, object-storage and message-queue configuration is not presented here as a completed integration. Private address restrictions also affect access to internal systems.

The browser SDK console is a bounded set of operations, distinct from running arbitrary Python. This recording shows the existing read-only agent-list operation and its actual response.

Test a permitted operation inside Aegis. The built-in testing screen reads a list of 18 assistants. This is an in-app list lookup; it does not show an external Python program running an agent. The displayed response time is one sample, not a benchmark.

Read-only assistant-list result in the built-in testing screen

Original in-app test, using fictional demonstration accounts.

Read the assistant list from the testing screen · 20 seconds
A permitted read-only example in the application’s built-in testing screen returns the recorded list of 18 assistants. This is a list lookup inside the application, not a separate external program or an assistant performing work.
Download the original recording or read its transcript

A permitted read-only example in the application’s built-in testing screen returns the recorded list of 18 assistants. This is a list lookup inside the application, not a separate external program or an assistant performing work.

  1. 00:00:00 — Run a permitted test that reads the list of AI assistants.
  2. 00:00:10 — The test returns all 18 assistants and shows how long the response took.

Download captions (VTT)

Download the original recording (embedded English remains).

For an external API or Python SDK evaluation, agree the operation, authentication and expected result for your deployment. A browser-console response does not establish that external client workflow.

06 · Knowledge and learning

Keep company know-how useful and controlled.

Give agents information your team has checked, and review changes before reusing them.

Approved knowledge

Publish policies and reference material with classification and access rules. Retrieval checks information clearance and organizational scope.

Reusable procedures

Assign the instructions an agent should follow. Share procedures within the configured department/team scope; publication does not grant additional authority.

Leadership instructions

Publish directives to selected units, track acknowledgement and replace or withdraw outdated instructions. Acknowledgement records receipt, not proof of compliance.

Turn experience into a reviewed procedure.

  1. Record Start with a captured agent run.
  2. Propose Ask for a reusable procedure from that work.
  3. Review Inspect and edit the proposed change.
  4. Accept Apply it only after a human decision.

This is a human-initiated workflow for improving instructions, not model retraining or automatic learning from every action.

Silent demo · captions includedRemove an unsupported step from a reusable method · 71 seconds
The unsupported step is removed, the checked instructions are saved and assigned, and a later answer uses all five headings.
Read the transcript

A recorded invoice review produces a draft instruction that assumes access to bank records.

The demonstration operator uses the owner account to accept the revised proposal; the library preserves the accepted instructions.

The later answer remains a saved response; missing payment proof stays unknown. This improves instructions and does not retrain the model or prove bank access.

Fictional demonstration. Edited recording; saved-record views are labelled.

  1. 00:00:00.000 — Start with a recorded invoice review.
  2. 00:00:03.548 — Fictional company and demo accounts.
  3. 00:00:07.000 — The original proposal assumes access to bank and payment records.
  4. 00:00:11.685 — This exact saved step is still pending review.
  5. 00:00:15.000 — Remove that unsupported step. Use only the information supplied.
  6. 00:00:25.000 — Accept the checked instructions.
  7. 00:00:28.507 — The demo operator uses the owner account.
  8. 00:00:33.000 — The saved proposal now says accepted.
  9. 00:00:40.000 — The checked steps stay in the library.
  10. 00:00:47.000 — The invoice assistant receives them.
  11. 00:00:51.154 — This screen checks setup; it runs no work.
  12. 00:00:56.000 — A later answer uses all five headings.
  13. 00:01:00.000 — Saved response shown on a review page.
  14. 00:01:04.000 — Missing payment proof stays unknown.
  15. 00:01:07.316 — These steps do not change the AI itself.

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Knowledge, learning and scope

Knowledge publication and procedure proposals have separate review paths. Tenant learning exclusions restrict what can enter approved knowledge; a new exclusion does not automatically erase all previously published material. Procedure selection follows department/team placement, and sharing does not confer authority.

The recording above shows a proposal, edited acceptance and later use. The Controls walkthrough separately shows knowledge publication, permitted and refused access, and acknowledgement of a leadership message.

Explore access and directive controls

07 · Operations

Know what ran, what it cost and what needs attention.

Trace an answer to its activity record, estimated cost and remaining budget.

Follow activity and cost

Review execution activity, work queues, budgets and cost breakdowns. Evaluate the records from an actual run, including any displayed estimates.

Operate the deployment

Configure runtime and gateway access, inspect logs and manage deployment state. Available controls depend on the selected hosting setup.

Reuse your organization structure

Import CSV or SCIM user data, or start from an Aegis structural export. Review the imported roles and clearances before assigning live work.

Watch one run’s cost and signed activity record · 50 seconds
Silent demo · captions includedCompare one answer with its usage and audit record · 50 seconds
The saved answer has a matching usage estimate and spending-limit record. The individual answer estimate is US$0.000895 against a US$1 limit.
Read the transcript

Request a handover using supplied fictional facts and no outside record changes.

After the answer, the app checks the signed record for changes.

The amount is an app estimate using saved prices, not a provider bill. The session total includes separate preparation and must not be equated with this answer’s cost. Signature verification is not human approval or proof of business correctness.

Fictional demonstration. Screenshot walkthrough; saved-record views are labelled.

  1. 00:00:00.000 — Ask for a handover using the supplied fictional facts.
  2. 00:00:05.347 — The request asks for no outside record changes.
  3. 00:00:10.000 — The assistant returns a summary of those facts.
  4. 00:00:15.054 — The saved answer belongs to this same request.
  5. 00:00:20.000 — The model reports how much text it handled.
  6. 00:00:24.433 — The app uses saved prices to estimate this run’s cost.
  7. 00:00:30.000 — This run uses the saved US$1 spending limit.
  8. 00:00:34.490 — The record shows the amount spent and the amount left.
  9. 00:00:40.000 — After the answer, the app checks the signed record.
  10. 00:00:44.766 — It checks for changes to the record. This is not a bill.

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Deployment and assurance detail

Enterprise deployments can use operator-provisioned dedicated organization data stores. This is not a live migration of an existing shared tenant, or a claim of separate infrastructure for every component.

Organization import is structural onboarding, not continuous directory provisioning. Deployment to a gateway requires a configured, reachable gateway. Automatic infrastructure scaling is not offered as an implemented capability in this evaluation.

Audit records, signed records and checks that prevent an action are different forms of evidence. Confirm the verification and enforcement timing for the chosen runtime and operation.

Deployment and data handling · Audit and authority

Your evaluation

Bring your architecture and one useful workflow.

Identify the systems, permitted actions, expected output and reviewer. We’ll use those to discuss the configuration and the evidence your team needs.