Confirm fixes the root cause – replacing gut-feel ratings with objective behavioral data. $18.2M raised to make reviews worth having.
ENTRY ANGLES
Platforms that analyze organizational network structure from communication logs (email, messaging, video calls) · Generate actionable insights from network analysis to improve performance and reduce attrition · Surface hidden talent and optimize processes using organizational network data
VERTICALS
CAPABILITIES
Organizational network analysis technology, Integration with communication platforms (email, messaging, video call systems), Data analytics and insight generation from interaction patterns
CONFIRM FOUNDER
“Who do you see as making an exceptional contribution?”
When performance review season arrives, a collective groan goes through most organizations. 64% of employees consider the process a partial or complete waste of time. Only 20% of companies describe it as genuinely effective and useful.
Confirm wants to end that misery – not by abolishing performance reviews, but by making them easier to produce and actually meaningful again. Their approach: ground the process in as much objective data as possible. (The specific method is covered below in "Why It Matters" – because that's where the interesting part lives)
What Confirm is explicitly *not* doing is traditional 360° feedback – the startup has literally crossed it out on their homepage.
The platform data can be used for more than just performance assessments:
- Designing targeted retention strategies for employees at risk of leaving - Uncovering hidden talent buried in the org chart
Showing employees their evaluation grounded in data – not subjective opinion – is also more persuasive. It gives them a sense of objectivity, prompts real self-reflection, and makes clear exactly what needs to improve.
The same data provides a stronger foundation for compensation decisions: pay and bonus adjustments based on demonstrated contribution rather than managerial impression.
Promotion decisions become cleaner too – comparing candidates on data rather than competing opinions.
And the same logic works in reverse: identifying underperformers for performance improvement plans or, ultimately, termination.
That said, data is only data. It can be interpreted multiple ways, and human context adds important nuance. Managers will still write performance reports – but now they receive AI-generated drafts from the platform. Reviewing and editing a draft takes roughly half the time of writing from scratch.
Pricing is per-employee subscription; exact figures aren't published on the site, which turns the pricing inquiry into a sales conversation.
Confirm has been operating for several years and counts Tucows, Canada Goose, and Niantic among its enterprise clients. The current round is $6.2M, bringing total funding to $18.2M across five rounds.
Traditional performance management evaluates individuals. But actual company results come from teams. And "teams" here doesn't mean formal org chart units – it means the real working network of people collaborating across departments and hierarchies.
Even people who sit in the same formal team may rarely actually work together. And the most high-impact collaborations often cut across org chart lines entirely.
This means a company that wants to understand *how* its people are really performing needs to first map the *actual* interaction network – who works with whom, how intensely, and in what patterns. Only then can it assess how effectively that network is functioning.
Deloitte gave this a name: Organizational Network Analysis (ONA).
One way to build the network map is to survey employees directly: "Who do you turn to for help and advice?" "Who do you see as making an exceptional contribution?" "Who seems to need support or attention?"
Another way is to extract it from the systems employees already use – counting who messages whom, how often, who appears in which meetings, and so on.
Analyzing the resulting network reveals distinct node types:
- Central nodes: employees connected to a large part of the organization – highly influential, but at risk of becoming bottlenecks. - Knowledge brokers: employees who bridge otherwise disconnected parts of the network, often across departments. Critical for information flow, but need active management to keep that flow under control. - Peripheral nodes: employees with few connections. Could signal a process design problem, a disengagement problem, or an overlooked talent who's silently underutilized – and at high risk of leaving.
This network view is a more objective and actionable lens on organizational health than individual manager opinions. The real question isn't whether any single employee is performing – it's whether the organization is functioning effectively as an interconnected system.
The clearest analogy is the story of the Oakland A's, told in *Moneyball*. The dominant baseball strategy was to recruit individual stars who showed the best personal statistics. The A's couldn't afford stars, and just lost the ones they had. But their coach partnered with a mathematician who had built a statistical framework for evaluating *team* effectiveness rather than individual brilliance. They filled the roster with undervalued players who fit the team's network of needs – and won an unprecedented 20 consecutive games, setting a league record.
Confirm is essentially Moneyball for HR and organizational management: replace subjective individual assessment with data-driven analysis of how the organization functions as a whole.
Performica – [covered here](/review/interesnaja-tehnologija-dlja-novogo-trenda) earlier this year – built a similar network analysis platform for a different use case: reducing turnover. When someone announces they're leaving, Performica identifies which colleagues are most tightly connected to them – so the company can take targeted retention action before the resignation triggers a domino effect. They raised $3M initially. Since then, Performica has expanded to include performance evaluation, building essentially the same capabilities as Confirm.
Using organizational network analysis well requires the ability to quickly, reliably, and continuously build a picture of how people actually interact inside the company. It can't be done once and left alone – the network shifts constantly.
Ironically, the most favorable conditions for this kind of analysis have emerged precisely in the remote work era. When people work in the office, much of the real interaction happens in hallway conversations and informal exchanges that leave no trace. Remote work forces almost everything through email, messaging platforms, and video calls – all of which are automatically logged, countable, and analyzable.
As remote and hybrid work becomes the norm rather than the exception, the share of trackable interactions keeps growing. That increases both the quality of network maps and the demand for platforms that build them and help companies act on them.
Few executives would turn down the chance to run their company like Moneyball.
The opportunity: build platforms that analyze organizational network structure and generate actionable insights – to improve performance, reduce attrition, surface hidden talent, optimize processes, and more.
The field is wide. The technology is ready. The timing is right.
And Confirm and Performica are there to inspire – and to copy from.