Automate your agency with an all-in-one AI Data Analyst
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+200K Professional Users
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+200k professionals using Conduit
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We’re Building the Future of Marketing and Sales, With AI Employees

Centralize Data
Save Time
Gain Accuracy
Analytics
Decision-making
Scale Rapidly
Reduce Budget
Centralize your multi-account data
No need to switch between hundreds of accounts in CRM applications and advertising platforms. Connect your clients' accounts and subaccounts, as well as spreadsheets with campaign plans, and view all the data on a unified dashboard.

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Redirect your time from manually inputting data into spreadsheets to focusing on generating revenue.
Each week, your team spends up to 30% of their time preparing reports. The AI employee automates all these tasks, allowing you to now focus on high-leverage activities like closing deals.

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Always have accurate data.
The AI employee cleans data, removes duplicate records, and filters campaign names. Additionally, the data is updated whenever changes occur at the source.

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Metrics are calculated exactly as you need them.
The AI employee is fully tailored to your individual preferences and goals. You specify the raw data to use and how it should be combined, and the AI generates the report you need.

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Meetings and decision-making are always efficient.
All the data you need for decision-making is available within seconds at any time. The data always aligns with the source of truth and contains no discrepancies. You can trust the data, enabling you to make decisions quickly and efficiently.

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Handle more clients with the same team.
The AI employee automates over 80% of your team's analytics workflow, doing it more efficiently. This frees up your ad ops and representatives to focus on high-impact activities like closing deals.

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Eliminate ad budget waste
Human managers often make mistakes when managing advertising campaigns. AI, on the other hand, doesn't make errors, ensuring that instead of wasting the budget without results, the advertising campaign generates profit.

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How Conduit helps teams work smarter and grow faster
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We had a spreadsheet with 100 tabs that my 5-person team updated every week, spending 30% of their time on it, and the spreadsheet was always broken.

Now, the AI Data Analyst prepares all the data for me in real-time, and the team is focused on clients and ad buying.
Mike Massey CMO @ The Implant Engine
About The Implant Engine: it is a healthcare marketing agency specializing in acquiring and converting high-quality leads for medical providers.
Results that drive.
Data that delivers.
Boosts marketing managers productivity
30%
Saved the Ad Budget Waste
10%
New Revenue
$1.2M
Cost Savings
$1M
ROI
370x

Business AI built to fit your workflow,
no matter who you are

The fastest way to implement AI Copilot and Reporting for your application

No-Code Solution

  1. Connect your database to Copilot.
  2. Create Workspaces for your users.
  3. Upload your assets to ensure the Copilot UI matches your application.
  4. Launch Copilot on your domain.

API Integration

  1. Connect your production data via API.
  2. Use user tokens within Conduit to control data access granularly.
  3. Integrate Copilot UI elements into your application via API or iframe.

Use Cases:

ETL Data Pipeline: Leverage hundreds of pre-built integrations and ETL pipelines to seamlessly connect various business applications with your application.

Embedded Reports in SaaS Applications: Integrate dashboards and LLMs into your application quickly and effortlessly.

Custom CRM: Offer your clients industry-specific reporting and a tailored transaction search engine.

AI Chatbot for your data: Integrate an AI chatbot into your website that is connected seamlessly with spreadsheets or a SQL database and answers questions of your visitors .

Niche AI Product: Create unique AI-driven products with specialized models or prompts without the need for extensive infrastructure or UI development.

Ad-Hoc Reports for Existing Reporting Solutions: Enable business users to ask ad-hoc questions about your BI system reports, saving time for both data analysts and users.

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