Jess was a wine bottle, slowly uncorked. Oh, this is about data? Had GeneticAlly brought her here to talk about algorithms?

“Alan’s great,” she said carefully. At the prospect that she was here for consulting, not because she had lemur DNA, the nausea slowly cleared.

Lisa gestured to an overly tanned man to David’s left. “Brandon Butkis is our head of marketing.”

Another hand closed around Jess’s, another face gave her an urgent, vibrating smile. All she could see was blindingly white capped teeth.

After Jess had shaken every hand in the room, Lisa gestured for her to sit down in the direct center seat at the table.

“It’s probably unexpected to walk into a full room like this,” Lisa started.

“A little,” Jess agreed, “but I know how important it is to get data organized, and how hard it is to do that when the data set is as big as yours.”

David and Brandon exchanged a quick look. Lisa’s smile slipped for only a second, but Jess logged it. “That’s definitely true. I’m sure you know that better than anyone.”

A man—Jess thought his name was Sanjeev—on the other side of the table caught Lisa’s attention. “Is Peña coming in for this?”

“He’ll be here,” Lisa said, and then turned to Jess. “Sorry to make you wait, Jessica.”

“Jess is fine,” she said, adding unnecessarily, “I mean, calling me Jess is fine.” Another awkward pause. “I wasn’t referring to myself in the third person.”

After some courtesy laughter, the room fell into a pin-drop silence. It seemed that everyone but Jess knew what this was all about, but no one could tell her until River had arrived. Unfortunately, no one knew where he was (“He said he was on his way up from his office ten minutes ago,” Sanjeev told the throat-clearing, paper-shuffling table).

Nor could anyone think of something to say. So of course, her mouth opened, and words tumbled out. “You all must be very excited for the launch.”

Heads bobbed around the table, and Brandon Butkis delivered an enthusiastic “Very!”

“Have you all given samples as well?” she asked.

There was a strange exchange of looks around the table before David said carefully, “We have, yes.”

Jess was just about to break and ask for some bloody information when the door burst open and River made a grand entrance much like his irritating, sweeping arrivals at Twiggs. “I’m here. What’s up?”

A tangible energy filled the room. Everyone sat up straighter. Every eye followed him as he moved to his seat. Yes, he was great to look at, but there seemed to be more to the weight of their attention, like the low, humming vibration of hero worship.

River’s gaze passed over the group, sweeping past Jess before pausing and jerking back to her face. “Why’s she here?”

“Have a seat, Riv,” Lisa said, then turned to a petite Asian woman to her right. “Tiff? Do you want to hand out the data?”

Data. Yes. Great. Jess’s shoulders eased, and she took a sheet when the stack came around.

The handout contained much less information than Jess would need to give useful feedback on a commercial undertaking of this scale. Two client IDs were listed at the top left and a red circle around a number in the upper right corner. Ninety-eight. Beneath was a table with a simple summary of a data set: variable names, means, deviations, and P values with many, many zeroes after the decimal.

There was a highly significant finding in this data; the urgency of this meeting was becoming clear.

River released a breath that sounded like it’d been punched out of him.

“Wow,” Jess said. “Ninety-eight. Is that a compatibility score? I realize I’m new to this, but that’s huge, right?” She flipped back to her memory of Lisa’s presentation. “Diamond?”

The nervous energy at the table doubled; all but one head nodded. River was still staring at the piece of paper.

“Yes,” Lisa said, and her smile was so intense the skin had grown tight around her eyes. “The highest we’ve seen in the DNADuo is ninety-three.”

“Okay, so are we asking about a way to confirm this interaction?” Jess leaned in, looking at the variables. “Without the raw data, I can only guess, but it looks like you’ve customized your stats using an N-type analysis—which is exactly what I would have used. But I’m sure you know the biggest problem with this is that the bounds we would normally use for a typical algorithm become less effective. Though”—she chuckled—“looking at this P value, I’m guessing with this pair the interactions are everywhere, even with stricter bounds. I could create a non-Euclidean metric, something like a multidimensional data structure—like a k-d tree or cover tree …” She trailed off, looking up. No one was nodding excitedly; no one was jumping in to brainstorm. Maybe there wasn’t another statistician in the room. “I’m more than happy to dig into your post hoc analyses, though with the number of genes in your array, I might need a couple weeks.”

Self-conscious now, she put the packet down on the table, smoothing it with her left hand. The room had grown so quiet, the sound of her palm over paper seemed to echo around them. But no one else was actually looking at their handout, or even seemed to be listening. They were all looking at River.

And when Jess looked at him, at the raw shock in his expression, a current of electricity ran through her, almost like she’d just touched a live wire.

He cleared his throat and turned to Tiffany. “Tiff, did you look through the raw data?”

She nodded, but she was staring at David, who was exchanging another heavy look with Brandon. The room felt deeply, meaningfully silent, and Jess realized she was missing an important context for the gravity here.

Awareness sank as quickly as a weight in water. Jess glanced down again at the client information.

Client 144326.

Client 000001.

Oh, God.

“Um … who is client number one?”

River cleared his throat; he’d gone sheet white and gripped the paper in two hands. “Me.”

Oh. Well, Jesus Christ, no wonder he wanted to confirm the analysis. A Diamond Match for the original scientist on the project was huge news, especially this close to launch.

“Okay, I get it.” Jess took a deep breath, leaning back, ready to get to work. “How can I help?”