Turn a vague “AI assistant” idea into a defined role, workflow and usable output.

We help configure task-specific assistants and agents for research, support, operations, content and internal knowledge. The work focuses on role definition, instructions, context, tools, actions, boundaries, output formats and testing.

View implementation packages See two concrete deliverables

Human-led setupTool and output designScenario testing

Direct answer

What is the difference between an AI assistant and an AI agent?

An assistant usually helps a person complete a task through instructions, context and structured outputs. An agent may also take or coordinate actions through connected tools, APIs or workflows. In practice, the important part is not the label: it is defining what the system may do, what information it can use, when it needs approval and what a successful output looks like.

Two concrete example deliverables

What a completed assistant or agent engagement can look like

These are sample scopes that show the work from discovery to handover. They are not claims about previous clients or guaranteed outcomes.

Deliverable A · Research assistant

Research and briefing assistant with source-aware outputs

For a team that repeatedly needs structured research briefs instead of inconsistent free-form answers.

Define the research jobSpecify the questions the assistant should answer, acceptable sources, recency expectations, audience and final brief format.
Design the operating instructionsCreate rules for planning research, separating facts from assumptions, handling missing evidence and showing source references when available.
Build reusable task templatesCreate prompts or input forms for competitor reviews, market scans, product research, meeting preparation or other repeatable research tasks.
Standardize the outputDefine sections such as summary, findings, evidence, uncertainties, recommendations and follow-up questions.
Test weak and ambiguous requestsEvaluate incomplete briefs, conflicting sources, unsupported claims, stale information and prompts that invite overconfident answers.
Refine and hand overAdjust instructions and provide a concise operating guide so the assistant can be used consistently by the intended users.

Typical outputs

Research assistant role and system instructions
Reusable research request templates
Source-handling and uncertainty rules
Structured research brief format
Quality-control test set
User handover guide

Typical fit: 3–6 sessions

Deliverable B · Operations assistant

Internal operations assistant for SOPs and recurring tasks

For a business that wants employees to ask operational questions and follow a consistent process without letting the assistant invent policy.

Map the operational use casesChoose the recurring questions and tasks the assistant should support, plus the topics that must remain human-controlled.
Organize approved knowledgeStructure SOPs, checklists, templates and policy material into a clearer knowledge set with ownership and update notes.
Configure role and boundariesDefine how the assistant should answer, when it should quote or summarize internal guidance and when it must ask for clarification.
Create task templatesBuild repeatable instructions for status summaries, handovers, checklists, document preparation or other internal workflows.
Test policy-sensitive casesCheck outdated procedures, missing context, conflicting documents, requests outside scope and cases requiring manager approval.
Document maintenanceProvide a simple process for updating source material, retesting high-risk prompts and communicating changes to users.

Typical outputs

Assistant role and scope definition
Knowledge organization plan
System instructions and task templates
Escalation / clarification rules
Operational test matrix
Maintenance and handover checklist

Typical fit: 6–10 sessions depending on knowledge volume

Scope note: tool calls, autonomous actions and integrations depend on the selected platform and available permissions. We do not promise fully autonomous behavior where the platform requires human confirmation or does not expose the necessary tools.

Before implementation

What we need from you

Clear use cases and representative examples are more valuable than a long list of buzzwords.

One or more target tasks

Describe the job the assistant should help complete and who will use it.

Representative inputs

Provide examples of questions, documents, briefs or situations the assistant will encounter.

Desired outputs

Show the format you want: summary, checklist, structured fields, email draft, research brief or another deliverable.

Approved knowledge

Share the source material the assistant may rely on and identify information that must not be used.

Tool constraints

Tell us which apps, APIs or automation tools are available and what actions require approval.

Failure examples

If you already have an assistant, show cases where it is inconsistent, too verbose, inaccurate or difficult to control.

Scope boundaries

Agents still need boundaries, testing and human ownership.

We can help make an assistant or agent more useful and repeatable, but third-party AI models may still make mistakes. High-impact decisions, sensitive data handling and regulated processes may require additional controls or professional review. The customer remains responsible for account permissions, approved data and the final use of generated outputs.

Related services

Connect the assistant to the rest of your AI stack

Agents become more useful when instructions, integrations and workflow boundaries are designed together.

Need a defined assistant instead of another generic chatbot?

Start with the job you want the AI system to perform.

We can help turn that job into instructions, outputs, tests and a maintainable workflow.

View AI support pricing