AI agent for b2b research agency owners
Create an AI LinkedIn company scoring agent with its own web page. Give your clients a ranked company shortlist with transparent qualification reasons.
Your method. Their task. A result they can use.
Your client starts a conversation.Your client describes the task through text or voice.
The page becomes their result.The agent makes the whole page the current result.
An AI LinkedIn company scoring agent is a customer-facing service that B2B research agency owners can offer to a client choosing accounts or professional roles to research. It delivers a ranked company shortlist with transparent qualification reasons. The client opens the agent's own page and URL, supplies company filters, ideal client criteria and permitted LinkedIn access, and works through the task by text or voice. With Agentplace, you supply the expertise and configure the tools behind this service.
Make the ranking explainable rather than treating a score as buying intent. Research the company or role against explicit criteria, retain sources and distinguish confirmed fields from assumptions. Explain the match rather than reducing it to an unexplained score. The client can change a criterion and inspect the resulting shortlist. Increase the minimum team size and rerank the same candidate set. The agent revises the affected result and keeps accepted details in context instead of making the client restart the entire task. The agent controls the content and components across its page so the result stays usable while the conversation continues.
Sell a prospect research session or a verified shortlist package. Export the agreed records and unresolved fields to the client's chosen CRM or sheet.
Start free with your business idea. Our AI builder can help you explore it, answer questions, and create your agent. No technical specification needed. Sign in to continue.
What you get
An AI LinkedIn company scoring agent is a customer-facing service that B2B research agency owners can offer to a client choosing accounts or professional roles to research. It delivers a ranked company shortlist with transparent qualification reasons. The client opens the agent's own page and URL, supplies company filters, ideal client criteria and permitted LinkedIn access, and works through the task by text or voice. With Agentplace, you supply the expertise and configure the tools behind this service.
Sell a prospect research session or a verified shortlist package. Export the agreed records and unresolved fields to the client's chosen CRM or sheet.
Ask about company filters, ideal client criteria and permitted LinkedIn access. Make the ranking explainable rather than treating a score as buying intent. Keep confirmed facts separate from missing information, and use your service rules to ask only the follow-up questions that change the result.
Research the company or role against explicit criteria, retain sources and distinguish confirmed fields from assumptions. Explain the match rather than reducing it to an unexplained score. The client can change a criterion and inspect the resulting shortlist. Increase the minimum team size and rerank the same candidate set. The agent revises the affected result and keeps accepted details in context instead of making the client restart the entire task.
Sell a prospect research session or a verified shortlist package. Export the agreed records and unresolved fields to the client's chosen CRM or sheet. Define the included work, any revision allowance and the specific continuation before clients begin. Source access must be permitted and configured. Public data or a fit score does not establish buying intent, contact permission or decision-making authority.
The same client session holds the brief, accepted decisions and current result. Make the ranking explainable rather than treating a score as buying intent.
Why it's the best fit
Deliver a ranked company shortlist with transparent qualification reasons while the client works with you online.
Make the ranking explainable rather than treating a score as buying intent. A conversational service lets the client clarify the brief, inspect the current result and change a requirement in the same session. The value is the completed work and usable interface, not a chatbot that only describes what could happen.
| Your AI LinkedIn company scoring agent One specialist. The whole client experience. | The extra workWith traditional tools Websites, fixed-flow apps, and chat widgets. |
|---|---|
| 01The client experience | |
| Complete the client task Make the ranking explainable rather than treating a score as buying intent. Research the company or role against explicit criteria, retain sources and distinguish confirmed fields from assumptions. Explain the match rather than reducing it to an unexplained score. The client can change a criterion and inspect the resulting shortlist. | With traditional toolsA page describing the service A conventional service page can explain the offer and collect a request. Producing a ranked company shortlist with transparent qualification reasons still needs a separate service process. The client does not get that work merely by reading examples or clicking a contact button. |
| Revise the result in context Increase the minimum team size and rerank the same candidate set. The agent revises the affected result and keeps accepted details in context instead of making the client restart the entire task. | With traditional toolsA fixed form or preset workflow A form can collect company filters, ideal client criteria and permitted LinkedIn access. Handling a changed requirement after the first result needs revision rules, connected state and an interface for the new version. Those parts must be designed around this specific service. |
| Keep the working result visible The whole page can present a ranked company shortlist with transparent qualification reasons, relevant evidence and the current choice. Text or voice directs the work while the agent updates the useful components. The score does not imply readiness to buy. | With traditional toolsA separate chat widget A chatbot can adapt its written answer. Keeping the actual document, comparison, media or service record synchronized with that conversation needs additional interface and action logic beyond a message transcript. |
| 02Everything that comes with your agent | |
| Use your expert method Apply your ideal-client criteria, permitted sources, evidence standards and export fields. Make the ranking explainable rather than treating a score as buying intent. Your service rules determine which sources matter, what the agent may deliver and when the available evidence is insufficient. | With traditional toolsA general-purpose answer A general assistant needs the client to provide the relevant method, source access and delivery rules. Without that setup it cannot reproduce the defined service just by recognizing the topic. |
| Work through text or voice Clients can explain company filters, ideal client criteria and permitted LinkedIn access in natural language and clarify the parts that affect the result. The agent can adapt its explanation to their language while preserving the same agreed task and visible outcome. | With traditional toolsSeparate conversational and visual flows A separate phone call, form and application can each help the client. Keeping their facts and decisions synchronized needs a deliberate connection between those experiences. |
| Deliver the selected service action Sell a prospect research session or a verified shortlist package. Export the agreed records and unresolved fields to the client's chosen CRM or sheet. Source access must be permitted and configured. Public data or a fit score does not establish buying intent, contact permission or decision-making authority. | With traditional toolsA result copied between tools Documents, email and specialist tools can deliver this work with the right setup. Maintaining the accepted version and action status across them is additional work the operator must coordinate. |
| Continue the same client session Keep the selected brief, source references and accepted decisions available within the configured client session. Increase the minimum team size and rerank the same candidate set. The agent revises the affected result and keeps accepted details in context instead of making the client restart the entire task. Returning clients can inspect the current version rather than compare disconnected answers. | With traditional toolsA fresh request without the prior decisions A new contact form or unconnected chat can require the client to supply the same information again. Continuity depends on a shared record and the correct access rules, not on a personalized greeting. |
Some traditional tools offer individual capabilities. Agentplace brings them into one AI service. Connect the payments, calendar, phone, CRM, and follow-up channels you want to use.
How it works
Define the service, test a complete client request and publish its page. The times shown are planning estimates. Materials, tool access and testing determine the real setup effort.
Provide your ideal-client criteria, permitted sources, evidence standards and export fields. Specify the inputs needed for a ranked company shortlist with transparent qualification reasons, including company filters, ideal client criteria and permitted LinkedIn access. Add a successful example and a request that lacks necessary evidence so the agent can distinguish a usable result from an unsupported one.
In this fictional example, Maya uses the service with a defined brief. Regional software firms. The client-defined scope drives selection. The sample company meets the stated range. Check the first result against the supplied facts. Then test this revision. Increase the minimum team size and rerank the same candidate set. Verify that the affected output changes while accepted details remain intact. Source access must be permitted and configured. Public data or a fit score does not establish buying intent, contact permission or decision-making authority.
Publish the agent's page and share its URL with clients. Sell a prospect research session or a verified shortlist package. Export the agreed records and unresolved fields to the client's chosen CRM or sheet. Configure only the source, payment and delivery connections needed for that offer. Test success, missing access and a failed external action so the page never claims a result that the connected system did not return.
Made for your kind of business
Sell a prospect research session or a verified shortlist package. You define the expertise and standards behind the offer while clients can obtain a ranked company shortlist with transparent qualification reasons directly through your agent.
Use your ideal-client criteria, permitted sources, evidence standards and export fields to make the delivered work inspectable and consistent. Make the ranking explainable rather than treating a score as buying intent. Keep the team focused on exceptions and additional work rather than reconstructing the brief from disconnected messages.
Build an offer around a ranked company shortlist with transparent qualification reasons. Start with one complete task and a defined customer group, then configure the evidence and tools that make that offer real. Source access must be permitted and configured. Public data or a fit score does not establish buying intent, contact permission or decision-making authority.
Your service, your starting point
The original task includes tools such as LinkedIn, Google Sheets, OpenAI. Choose and configure the providers required for your offer. These names describe connection options, not a claim that every integration or older model version is included or currently available. Choose the relevant apps below and connect the accounts your agent should use.
Start with my expertiseConnect the relevant publishing action. Connect the relevant account and choose which records and actions the agent can use.
Find source material for the client's question. Connect the relevant account and choose which records and actions the agent can use.
Read papers and documents the client shares. Connect the relevant account and choose which records and actions the agent can use.
Apply your research framework. Connect the relevant account and choose which records and actions the agent can use.
Organize evidence and source comparisons. Connect the relevant account and choose which records and actions the agent can use.
Book a research review with your team. Connect the relevant account and choose which records and actions the agent can use.
Integrations
Connect the tools you use to deliver this service. Your agent can use their records and actions while helping clients on its own page. Choose the relevant connections below and decide what it can read, create, or send.
Your expertise.
Their personal result.
One connected service.
Agentplace connects to business tools through Composio's catalog of over 1,000 integrations. These six examples are a starting point. Choose the apps and actions your agent needs while clients keep working on its page.
Available connections depend on the app's API and your account permissions.
Browse the integration catalogConnected agents
Your AI LinkedIn company scoring agent stays with the client. It can pass a defined part of the work to your separately connected ChatGPT or Claude agents and bring their result back into the same service session. Your client does not need to manage those internal tools.
A supporting agent can check the accepted result against your ideal-client criteria, permitted sources, evidence standards and export fields and return discrepancies with evidence. Your public agent keeps the client brief and current result in view.
Your shortlist ranks fit before company size
The client-defined scope drives selection. Your expertise.
Their personal result.
One connected service.
A few things to know
An AI LinkedIn company scoring agent is a customer-facing service that B2B research agency owners can offer to a client choosing accounts or professional roles to research. It delivers a ranked company shortlist with transparent qualification reasons. The client opens the agent's own page and URL, supplies company filters, ideal client criteria and permitted LinkedIn access, and works through the task by text or voice. With Agentplace, you supply the expertise and configure the tools behind this service.
A ranked company shortlist with transparent qualification reasons. Research the company or role against explicit criteria, retain sources and distinguish confirmed fields from assumptions. Explain the match rather than reducing it to an unexplained score. The client can change a criterion and inspect the resulting shortlist. The current result is presented through the agent's own interface, so the client can inspect it and ask for changes instead of treating a message thread as the final deliverable.
Make the ranking explainable rather than treating a score as buying intent. Research the company or role against explicit criteria, retain sources and distinguish confirmed fields from assumptions. Explain the match rather than reducing it to an unexplained score. The client can change a criterion and inspect the resulting shortlist. The agent performs the configured service and updates the result on its whole page. A separate chat widget can answer questions, but connecting those answers to the active service record, visual result and tools takes additional implementation.
Provide your ideal-client criteria, permitted sources, evidence standards and export fields, together with examples covering company filters, ideal client criteria and permitted LinkedIn access. The original task includes tools such as LinkedIn, Google Sheets, OpenAI. Choose and configure the providers required for your offer. These names describe connection options, not a claim that every integration or older model version is included or currently available. Source access must be permitted and configured. Public data or a fit score does not establish buying intent, contact permission or decision-making authority.
Increase the minimum team size and rerank the same candidate set. The agent revises the affected result and keeps accepted details in context instead of making the client restart the entire task. The agent explains the implications and keeps the accepted version distinct from a proposed revision.
Sell a prospect research session or a verified shortlist package. Export the agreed records and unresolved fields to the client's chosen CRM or sheet. Explain the service scope and configure the relevant payment or delivery provider before offering it to clients. Payment for the agent's work is distinct from third-party usage costs or a separate purchase.
No. It is a static fictional example. Client names, records, source observations and results shown in the preview are illustrative. Create your own agent, provide your knowledge and configure the required tools to offer this service.
It runs on Agentplace. Agentplace is an AI agent platform where the agent gets its own page, talks to your visitors there, and carries the request through to the end instead of handing it to a form. You can open this template and change any step before you publish it.
Turn your expertise into a service clients can use
Create an AI LinkedIn company scoring agent with its own web page. Give your clients a ranked company shortlist with transparent qualification reasons.
Create my AI agent
Create my AI agent