Openprise

05/29/2026

Most ops teams don't have a tools problem.

They have a data problem. Duplicates that slip through. Enrichment that covers 60% of records, not 100%. Leads that sit in a queue for 48 hours before anyone touches them.

The tools were supposed to fix it. Instead, they multiplied it.

Palo Alto Networks got their match rate above 85%. Nutanix saw a 70% improvement in rep-to-record alignment. Teladoc Health stopped getting cornered into point solutions and built something they could actually grow with.

Different teams, different stacks. Same result: data they could build on.

If patching things isn't working anymore, it's worth a conversation.

chat with us: https://www.openprisetech.com/request-a-demo/?utm_medium=organic-social&utm_source=facebook

05/22/2026

Opie learned some new tricks. 🐙
We just launched an AI-powered chatbot on the Openprise website — and it's not your typical "How can I help you today?" experience.

It's trained on our product docs, customer stories, and technical architecture. So whether you're evaluating data orchestration tools, trying to explain Openprise to your boss, or just curious how AI orchestration works in practice — you can skip the PDF and just ask.

Try it. Ask Opie how multi-vendor enrichment pushes match rates from 50% to 88%. Or what a composable MAP architecture actually looks like. Or how AI bot detection catches fake form fills before they hit your CRM.

Fair warning: Opie may also try to convince you that octopuses are the most intelligent creatures on the planet. That part is not AI-generated. That part is just facts. 🐙

05/22/2026

Ever seen what lands in a free-text form field?

"just looking." "my boss made me fill this out." "asdfasdf."

Ops teams add "Other. Please describe." to get more context. What they actually get is unroutable chaos.

Here's the thing: AI can read that mess. Categorize the intent. Hand clean, structured data to your routing rules, even when the input looks like a toddler got to the keyboard.

Rules handle the clean data. AI handles everything else. That's the workflow.

Watch the skit above to see the pain (and the fix) in action. Sound familiar? Drop a comment.

05/20/2026

Everyone wants to talk about AI agents. Nobody wants to talk about what actually has to exist underneath them.

Here's what we keep seeing from ops teams at companies like Adobe, CrowdStrike, and Rippling: AI readiness isn't a switch you flip. It's a stack you build. And most teams are trying to build from the top down.

The hierarchy: get your data unified (Layer 1), clean it (Layer 2), orchestrate your workflows (Layer 3), then apply AI with intention (Layer 4), and finally, agents (Layer 5).

Most teams skip straight to Layers 4 or 5. That's not an AI problem. That's an architecture problem.

Where is your team on this stack? Drop a number in the comments.

05/20/2026

GIVEAWAY TIME 🥳

We're giving away a FREE 1-year membership to the RevOps Co-op Rise community (a $756 value).

If you work in ops, this one's for you.

Here's what you get:
✅ New member welcome kit
✅ Expert-led workshops
✅ Access to their Slack community
✅ Monthly career coaching sessions
✅ Resume and LinkedIn profile reviews
✅ Full access to the Career Growth Hub
✅ Small group accountability pods

That's mentorship, community, and career development all in one place.

How to enter:
→ Follow Openprise on LinkedIn
→ Drop a 🐙 in the comments

Big congrats to our recent winner, Michael Letendre 🎉

That's it!

Winner will be chosen at random on June 8th.

Good luck!

05/19/2026

Adobe Summit confirmed what we keep hearing in every conversation: the AI advantage isn't about which model you pick. It's about the data feeding it.

Josh Redner, our Director of Sales, wraps up our Adobe Summit series with the real talk — what it actually takes to move from AI experiments to AI that runs in production across your GTM stack.

Fragmented data silos. Manual enrichment. Routing that breaks at scale. That's what keeps teams stuck in pilot mode. Openprise automates and unifies all of it so you can integrate AI into your GTM strategy with confidence.

What would AI-ready GTM data unlock for your team? Watch and let us know in the comments.

05/18/2026

Your lead fills out a form. They're ready to talk. 🙋
Marketo says: "I'll get to it."
(Spoiler: it doesn't get to it.)
We made a skit about this exact problem — the Marketo-to-Salesforce handoff that quietly kills hot leads before sales ever touches them.
Marketo batches. It queues. It moves on its own timeline, not yours. And meanwhile, your lead is just... waiting.
Openprise automates that handoff so leads go to Salesforce immediately — not when the queue gets around to them.
Click to see exactly how it works: https://openprise.storylane.io/share/3nt504cmda4j?utm_medium=organic-social&utm_source=facebook&utm_campaign=storylane&utm_content=marketo-lag

05/14/2026

Most MAPs become junk drawers because they're asked to do two jobs — and it's costing MarketingOps teams more than they realize.

When one tool is handling both data ops (routing, scoring, deduplication, enrichment) and engagement (emails, nurtures, campaigns), you end up with slow workflows, brittle integrations, and technical debt that blocks every AI initiative on your roadmap.

The fix doesn't require starting from scratch. For most teams it's a hybrid model — keeping the MAP as the activation layer and moving data ops into a separate layer built for it.

We covered all of it in our Composable MAP webinar with Alyssa Hewitt and Len van Hoogenhuijze from CRMT Digital. When composable makes sense, what the hybrid model looks like in practice, and how to migrate in phases without disrupting campaign ex*****on or lead flow.

Worth watching if your MAP is carrying more than it should.
Watch on demand: https://www.openprisetech.com/resources/videos/webinars/is-your-map-a-junk-drawer-the-case-for-composable-architecture/?utm_medium=organic-social&utm_source=facebook&utm_campaign=webinar-crmt-2026-04-map-architecture

The “all-in-one” marketing automation platform (MAP) has become the junk drawer of the GTM stack. To thrive in tomorrow’s world of AI and data complexity, organizations must move from monolithic platforms to a composable architecture that separates the orchestration of data from the orchestrat...

05/12/2026

Your SDR team loves Clay. Your ops team? Less thrilled.

Here's the pattern: SDRs build beautifully enriched prospect lists in Clay. Those lists hit the CRM. And suddenly ops is drowning in 400 duplicate accounts because "Cisco Systems Inc." and "Cisco" and "Cisco Canada" all came in as separate records. Job titles all over the place. Leads routed to reps who left three months ago.

The problem isn't Clay. Clay does what it does really well.

The problem is what happens after the data enters your systems of record.

That's where Openprise comes in. Two tools. One pipeline. Full breakdown: https://www.openprisetech.com/blog/openprise-and-clay-for-ops/?utm_medium=organic-social&utm_source=facebook&utm_campaign=blog-post&utm_content=clay

GTM teams at Rubrik and JumpCloud use Clay and Openprise together for agility, governance, and scale. Get a sneak peek into their workflows.

05/12/2026

Here's the real reason most AI projects don't make it past the pilot stage — it's not the model, and it's not the budget.

It's the data pipeline nobody thought to fix first.

Ryan Nelson, our Sr. Director of Solutions Engineering, said it best at Adobe Summit last week: AI is only as reliable as the data it reads. Build on a broken pipeline and everything on top of it is fragile.

The teams getting AI right start with clean data and a pipeline that actually works. That's the foundation everything else runs on.

Is your data pipeline ready for AI? Drop your thoughts below. 👇