Instantly Understand Campaign Requirements and Delivery Risks

Reduce setup time and avoid delivery issues with AI-generated summaries of campaign requirements, validation rules, and configuration risks.

Launching campaigns often requires teams to interpret complex validation rules, understand required lead attributes, and configure multiple workflow components correctly.

Today, this can involve manually reviewing forms, validation jobs, and campaign configuration logic, slowing down onboarding and increasing the risk of setup mistakes or lead rejection later in the delivery process.

This feature helps teams understand campaign requirements instantly, identify potential misconfiguration earlier, and reduce the operational effort required to launch campaigns successfully.

Convertr AI generates intelligent summaries of campaign setup requirements, validation logic, forms, and QA configuration in plain English.

Users can quickly understand what data is required for a campaign, how validation is being applied, and where potential configuration risks may exist.

The feature is designed to help teams onboard campaigns faster, configure workflows more confidently, and communicate campaign requirements more clearly to suppliers and operational teams.

 Reduce the time required to understand and configure new campaign requirements 
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 Identify potential setup issues before they create delivery problems 
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 Eliminate manual investigation across forms, QA jobs, and campaign configuration
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 Help external suppliers understand campaign expectations and submit valid leads first time

Convertr Connect: AI Summaries

From Fragmented Validation to Intelligent AI QA

Replace complex, multi-step validation setups with a single AI-powered quality assurance layer.

Today, ensuring data quality in Convertr often requires stacking multiple validation and transformation Jobs to achieve the desired outcome. While powerful, this approach can be complex, time-consuming and reliant on specialist knowledge to configure correctly.

This leads to inconsistent validation across campaigns, slower setup times and challenges scaling across different use cases such as content syndication, events and global campaigns.

By introducing an AI QA Agent at the core of our processing layer, we can consolidate these fragmented processes into a single intelligent system. This reduces complexity, improves consistency, and enables a more scalable, AI-native approach to data validation.

The AI QA Agent replaces multiple validation and transformation Jobs with a unified, intelligent quality assurance layer.

Using a combination of predefined best practices and AI-driven decisioning, the agent can:

This creates a more streamlined and reliable approach to data validation, while maintaining flexibility for different campaign requirements.

 Replace multiple validation jobs with a single intelligent agent
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 Apply standardised, best-practice validation across all campaigns
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 Minimise the need for specialist configuration knowledge
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 Handle edge cases and complex scenarios more effectively than rule-based systems
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 Support content syndication, events, and global campaigns with greater consistency

In future we plan to expand the capabilities to include...

AI QA

Instant, Actionable Diagnosis of Lead Rejections helping Maximize Revenue

Stop guessing why leads failed - get instant, actionable insights to fix data issues and recover delivery performance faster.

When leads are rejected by a client, suppliers often waste hours trawling through hundreds of rows of data to understand the reasons for invalidation.

This slows down issue resolution, creates operational inefficiencies, and increases the risk of under-delivery against campaign targets.

This feature eliminates that manual investigation by providing an instant, aggregated view of why leads are failing so teams can quickly identify issues, prioritise fixes, and recover delivery performance faster.

Convertr AI analyses rejected leads and automatically groups them by error category and frequency, providing a clear operational diagnosis of the main causes of invalidation.

Instead of manually reviewing individual records, users can instantly understand why leads are failing, identify recurring patterns, and focus effort on the issues most likely to improve acceptance rates.

 Recover lost value by identifying and fixing invalid leads faster, helping ensure delivery targets are achieved
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 Eliminate manual debugging and instantly understand why batches of leads failed without reviewing hundreds of individual records 
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 Avoid wasting time on leads blocked by duplication rules or suppression lists and prioritise the records that can still be accepted
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 Convert complex invalidation patterns into simple, actionable operational insight

AI Assistant: AI Summary (for Invalid Leads)

Smarter Campaign Setup — AI‑Powered Enrichment & Integration Job Support

Translate natural language requests into fully configured Enrichment and Integration Processr Jobs with the Convertr AI Assistant.

Configuring Processr Jobs to enrich lead data or integrate with third‑party systems can be complex, requiring detailed understanding of each Job’s purpose, parameters and best practices. While this flexibility is powerful, it can also be difficult and time‑consuming for users who aren’t familiar with every Job type or integration pattern.

By extending the Convertr AI Assistant’s Jobs agent to include support for Enrichment and Integration Jobs, we’re removing that barrier. Users can describe the outcome they want in plain English and the assistant will guide them through setup or even apply recommended configurations where appropriate — simplifying workflows and boosting productivity.

This enhancement expands the AI Assistant’s ability to understand and configure a broader set of Processr Jobs including:

The assistant will explain what each Job type does, recommend relevant configuration options based on your natural language description and provide guidance or validation to ensure the setup aligns with best practices. With your explicit approval, it can also implement those configurations automatically.

 Turn plain English instructions into complex Processr Job setups
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 Append valuable external data to leads without needing deep Processr expertise
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 Configure reliable lead delivery into external systems with confidence

More general support available directly from within the AI Assistant.

AI Assistant: Support for Enrichment and Integration Jobs

Bring Convertr AI to Where You Work with MCP-Powered Assistant Integration

Access and execute Convertr workflows directly from your preferred AI tools and collaboration platforms.

Campaign setup, data requests, troubleshooting and day-to-day collaboration often happen outside Convertr in tools like Slack, Microsoft Teams or enterprise AI assistants. Today, this creates friction - users must switch back into Convertr or rely on manual processes to complete tasks.

By introducing MCP (Model Context Protocol) support for the Convertr AI Assistant, we remove this barrier. MCP allows Convertr capabilities to be securely exposed to external AI environments using a standardised approach. This means users can interact with Convertr through the tools they already use, reducing context switching and making workflows faster and more seamless.

This feature introduces an MCP layer that enables the Convertr AI Assistant to integrate with external AI clients and collaboration tools.

Through MCP, Convertr capabilities can be accessed and executed from environments such as AI assistants, chat platforms and other MCP-compatible systems. Rather than building one-off integrations, MCP provides a scalable, standards-based way to expose Convertr functionality.

This allows users to perform tasks such as retrieving data, configuring campaigns or running checks without needing to log into the Convertr platform directly.

 Access Convertr capabilities without leaving your existing tools 
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 Eliminate the need to move between systems to complete tasks 
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 Leverage a standards-based approach rather than bespoke integrations
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 Enable more advanced, AI-driven and agentic ways of working over time

MCP For AI Assistant (Reporting capabilities)

Click the tabs below to see what we're working on now and next. Full release notes can be found by clicking the link in the top-left corner of the page.

Convertr Roadmap