OpenAI SMB Channel Partner

Move beyond drafts and summaries.

ChatGPT Business is useful on day one. Aiterna helps your team move past one-off prompts into connected knowledge, custom agents, workflow automations, and habits that change how work moves.

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ChatGPT-ecosystem connector — LiveUses OpenAI's models

The assessment routes setup, agents, training, and workflow build recommendations.

01ChatGPT Business setup
02Custom agents for real workflows
03Adoption, training, and measurement

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OpenAI SMB Channel Partner · Shopify Partner

AI products in production

UK · Türkiye

The prompt-only ceiling

Your team has ChatGPT. The workflows still live outside it.

Drafts and summaries help individuals. Workplace AI connects the team workspace to approved context, defined agents, repeated handoffs, and operating rules, so AI becomes part of how work moves.

Current shallow usage

email drafts
document summaries
research snippets
one-off prompts
disconnected tabs
no workflow change

What changes

shared context
defined agents
repeated workflows
controlled automations
team training
measurement

Moving past prompts is the whole job — and it's the part most providers skip.

Setup and controls

Set up the workspace before you scale the habit.

A ChatGPT Business seat is the starting point. We make it a working part of your day.

ChatGPT Business is the starting point. Aiterna helps structure the workspace, explain the settings, connect context deliberately, and roll AI out with the right controls in place.

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Seats and onboarding

The right number, set up and ready, with admin you control and a workspace structured for how the team works.

Business data controls

We explain the relevant settings in plain language and help the team use them consistently.

Workflow selection

We pick the first workflows worth connecting, then train the team and measure what's actually used.

Agents

Agents are built around work, not novelty.

Agents are AI assistants built around a real workflow: your context, your documents, your tone, your steps.

Knowledge agent

trigger: A question about policy or process
agent output: An answer from approved company context
human decision: The team confirms and acts

Customer response agent

trigger: An inbound customer message
agent output: A drafted reply in the team's tone
human decision: A person reviews and sends

Sales follow-up agent

trigger: Notes from a call or meeting
agent output: A timely follow-up draft and next steps
human decision: The owner edits and sends

Document agent

trigger: A document to draft or review
agent output: A first pass against your defined workflow
human decision: A person checks and finalizes

Operations agent

trigger: A recurring update or handoff
agent output: A prepared summary and task list
human decision: The team approves and routes

Leadership briefing agent

trigger: Scattered activity across the week
agent output: A clearer operating view
human decision: Leadership decides where to focus

Outcomes by industry

What changes for a business like yours.

Agents and workflows stay abstract until you map them to the work a team already repeats. Pick an industry to see where the leverage tends to show up — and which capability drives it.

Less time assembling the deliverable, more on the judgment inside it.

Repetitive work today

proposals and scopes rebuilt from scratch
call notes typed up by hand
client status updates pulled together late

Where the leverage shows up

Proposals and scopes drafted from your past work and templatesCustom agenttime-to-first-draft
Call notes turned into follow-ups, action items, and a recap the same dayAgentic workflowfollow-up turnaround
Client-ready status updates assembled from scattered project activityCustom agentstatus-report prep time
The team answers from one approved knowledge base instead of hunting drivesChatGPT Businessknowledge reuse

Directional signals show the metric each move is designed to shift — not a guaranteed result. Your real starting point comes from the assessment.

don't see your industry? the assessment maps yours →

By team size

The rollout changes with the size of the team.

1 seat

Self-serve start

referral-link start if available
setup guidance
light onboarding content

5+ seats

Guided setup

setup assistance
initial workflow mapping
rollout guidance

20+ seats

Full onboarding

onboarding and team training
2 custom agents built free
+1 free custom agent for every additional 5 seats

In-person onboarding depends on geography, availability, and final engagement scope.

start the assessment See pricing →

Training and measurement

Adoption is measured in changed work, not logins.

The goal is not to make everyone prompt more. The goal is to identify repeated work, connect the right context, build useful agents, train the team around real tasks, and measure whether the system is becoming part of operations.

active workflows
repeated use cases
agent adoption
reduced manual handoffs
team confidence
leadership visibility

Proof, not promises

The team setting up your AI ships AI in production.

On the workplace side, the relevant proof object is CG03: a ChatGPT-ecosystem connector that supports connected AI workflows using business context.

CG03live

ChatGPT-ecosystem connector

A ChatGPT-ecosystem connector that supports connected AI workflows using business context.

Uses OpenAI's models.

See all proof

Honest answers

What owners ask us.

See where your team should move beyond prompts first.

The assessment maps your current AI usage, team size, workflows, data sensitivity, and goals — then routes the next step.

start the assessment

Start with the first workflow your team repeats every week.