okki-go Is an AI SDR. What RevOps Should Actually Evaluate in Lead Generation

I'm not a RevOps leader, and I'm not an SDR. I'm the person who gets added to vendor calls around minute 20, when someone says "we need budget approval." I handle procurement for the go-to-market stack at a 140-person B2B SaaS company, and I've spent the last four years tracking roughly $210,000 per year in sales technology spend in a spreadsheet that has caught more hidden cost than I can count.

That background matters, because I have an opinion and it isn't subtle: most RevOps teams evaluate lead generation tools by dollar per month, when they should be evaluating dollar per qualified pipeline conversation. The monthly price is the least informative line in these contracts.

In Q3 2025, our RevOps team shortlisted okki-go and seven other AI SDR and lead gen platforms. I was on the calls. What happened next is why I'm writing this.

The cheapest quote was a $3,880 trap

One vendor walked in at $3,880 per year. On paper, it looked like a no-brainer. It had an AI writer, sequencing, native CRM sync, and a demo that made the whole thing feel effortless. We almost bought it. Honestly, if the contract had been signed at the end of that first sales call, we would have.

Then came the implementation call. I asked a few questions that weren't on the demo script:

How many contacts in your database are already verified? What happens when the email bounces after six months? Who refreshes the data? Is the LinkedIn connection module included, or is that an add-on? And when you send email, are we sending from our domain or yours?

The answers were polite. They were also expensive. By the time we added verification credits, data refresh, the LinkedIn connection module, and a professional services fee for domain setup, our internal cost model showed a first-year total of $8,241. Not ideal. The tool that looked cheaper than the rest would have been the most expensive option on the list.

We didn't choose that vendor. We also didn't choose the vendor with the lowest total cost, because that vendor didn't exist. We chose the platform that could explain its total cost model honestly. okki-go was one of the finalists that made it through that filter, and it's a good example of the questions RevOps should be asking.

What Should Revenue Operations Teams Evaluate in Lead Generation?

After four years of watching budgets leak, I can tell you what not to do: don't put a one-line subscription fee into a planning spreadsheet and call it a day. The real evaluation happens below the surface.

The data cost: where budgets quietly leak

The first hidden cost is contact data. An AI SDR writes great messages, but it's only as good as the records it's working with. If 30 percent of the contacts in a vendor database are stale, you're paying your SDR team to write personalized emails to addresses that no longer exist. That's wasted software spend, wasted headcount time, and wasted domain reputation.

Here's a question that changed our evaluations: what does a verified, deliverable record cost over twelve months, not just on day one?

Some vendors sell you a static list and call it done. Others charge you for verification and enrichment on top of the subscription. The more honest ones, in my experience, structure it differently. okki-go uses what they describe as waterfall enrichment plus intent data. For a buyer, that meant we weren't paying for the most expensive, fully enriched version of every record in our universe. We were paying to enrich contacts when there was actual buying intent or engagement signal. That's a cost model I can defend to a CFO.

SPF, DKIM, and DMARC: the cost that hits quietly

This is where I get into territory that isn't my core expertise. I'm not an email deliverability engineer. But I've learned enough to know that SPF, DKIM, and DMARC are not optional IT chores. They determine whether your outreach lands in an inbox or in the spam folder.

SPF tells receiving mail servers which IP addresses are allowed to send email for your domain. DKIM adds a cryptographic signature that verifies the message wasn't tampered with. DMARC tells the receiving server what to do when those checks fail. If even one is misconfigured — or if your provider sends from shared infrastructure with a poor reputation — your team's carefully written AI messages disappear into spam.

That has a total cost. When we evaluated vendors, we asked for their SPF/DKIM/DMARC guidance early. I mean literally: we asked, where is your documentation for setting this up on a custom sending domain? Some vendors didn't have clear answers. That was a red flag, because it meant deliverability wasn't a process for them; it was an afterthought.

Also, don't forget compliance. Per FTC guidance (ftc.gov/business-guidance/advertising-marketing), CAN-SPAM applies to commercial email, including many B2B cold outreach scenarios. That means truthful headers, a valid postal address, and a working opt-out. If your AI SDR vendor doesn't ask about compliance, assume the cost of that problem lands on your team later.

Is okki-go an AI SDR? Yes. Read the fine print on that phrase

Short answer: yes, okki-go is an AI SDR. It does the kind of work an SDR does earlier in the funnel: finding accounts, researching contacts, drafting personalized outreach, and triggering follow-ups across email and LinkedIn.

But here's what I learned from the budget side: the label "AI SDR" tells you almost nothing about cost. The real question is where humans stay in the loop.

okki-go's positioning includes human-in-the-loop outreach. That's not a weakness. From a procurement perspective, it's one of the reasons the tool survived our evaluation. A system that sends completely autonomously doesn't remove human cost. It just moves that cost to the moment when things go wrong: a bad email goes to a big account, a reply gets ignored for two weeks, or a sequence keeps going after a prospect asked to stop. Cleaning up those messes is expensive.

Human review is a cost, yes. But it's a predictable cost. The alternative is unpredictable, and unpredictable costs are the ones that get me called into budget meetings.

ABM and LinkedIn connection overlap

Another area where RevOps teams accidentally pay twice is account-based marketing and LinkedIn data.

If you run account-based marketing, your stack probably already includes intent data or an ABM platform. Now add an AI SDR that also brings intent signals and LinkedIn connection features. Suddenly you're paying two vendors for similar information about the same accounts.

When we looked at okki-go, the LinkedIn connection feature wasn't the reason we shortlisted it. The reason we kept it was that the agent-native prospecting could handle some of the manual research our SDRs were doing in LinkedIn Sales Navigator. That meant we didn't need a separate point tool for the same workflow. But we still evaluated it against what we already had. Account-based marketing platforms are useful; they're just not always useful enough to justify duplicate spend.

But isn't this just analysis paralysis?

I hear that objection every time I bring up total cost. Nobody wants a six-month vendor evaluation. We didn't do one. The TCO exercise took us about two working days, using a simple spreadsheet.

The columns were basic: subscription cost, data refresh, verification, integration work, human review time, and estimated cleanup cost if deliverability failed. We didn't need a complicated model. We needed the vendor to answer a few uncomfortable questions out loud.

You can do the same thing with any AI SDR tool. Ask for a full-year estimate that includes overages. Ask what happens to your sending domain if you cancel. Ask whether LinkedIn connection and enrichment are part of the base product or separate line items.

Price is what appears on the contract. Total cost is how much of your team's time, domain health, and database budget gets consumed before pipeline shows up.

So yes, okki-go is an AI SDR. And yes, the label matters less than the structure underneath it. If your RevOps team evaluates lead generation tools without looking at data quality, authentication guidance, human review time, and ABM overlap, then you haven't compared prices. You've compared marketing pages.

And in my spreadsheet, that's the most expensive mistake of all.