Every HR stack is missing the same thing: a person whose job is to notice, intervene, and translate signals into action. We are that layer.
We are raising a pre-seed round to prove the Coordinator model, develop the platform, and grow the team.
There is a system of record for who you have worked with.
We are the system of record for who you actually work with.
The relationships inside your organization that drive retention, belonging, and culture. No platform tracks them today.
Gen Z workers are highly digitally connected yet, according to the U.S. Surgeon General's 2023 advisory, among the most isolated. They will not stay in places where they do not belong. Belonging is now a retention lever, not a perk.
Source: U.S. Surgeon General's Advisory, Our Epidemic of Loneliness and Isolation (2023).
When firm-wide remote work scaled at Microsoft during the pandemic, collaboration networks became more siloed and cross-team interaction dropped significantly. The hallway is gone. Most tools sold as replacements have plateaued or been discontinued.
As technology takes on more individual output work, the reason people stay becomes almost entirely relational. Companies that build genuine belonging keep their best people. Competitive, not soft.
We are pre-PMF and focused on learning. The current priority is validating problem-solution fit with a narrow ICP and accumulating the structured intervention data that anchors every later phase. Specific traction figures are shared in direct investor conversations.
Mid-market companies where culture is a CEO-level priority but there is no dedicated function to hold it. The Head of People is the buyer. Remote and hybrid teams are the sharpest fit, where the loss of organic interaction is most acute.
Active discovery conversations underway with Heads of People, culture leaders, and DEI practitioners across target-ICP companies. Each conversation tests the thesis and sharpens the Coordinator model.
Inbound interest from the site and warm introductions is converting into pilot conversations. A waitlist is forming as the category language resonates with the right buyer.
Over the next 60 to 90 days: converting pilot conversations to paid engagements, capturing structured intervention data from live cohorts, and validating the repeatability of the Coordinator role beyond the founder.
CultureConnect is a tech-enabled services company that sells outcomes — cultural connection, retention — on a recurring basis, with software as the leverage layer that lets each Coordinator support increasing numbers of customer accounts over time.
One Coordinator manages a focused set of company accounts. Fully hands-on. This is intentional: we are building behavioral data while delivering measurable outcomes.
OUR ASPIRATION: build software that supports the Coordinator on routine tasks over time, so each Coordinator can support more accounts. The path will be shaped by what real engagement patterns teach us. Not a current capability.
Multi-Coordinator deployment for enterprise customers. Software handles routine work (matching, scheduling, signal aggregation, brief generation) so each Coordinator manages substantially more accounts. AI augments the Coordinator's judgment — surfacing what to notice — but never replaces the human relationship at the employee level. Healthy unit economics at scale through Coordinator productivity, not Coordinator elimination.
Every Coordinator action is captured as structured data: the signal, the context, the intervention, the outcome. Over time, that data becomes the engine of Coordinator productivity — and a moat competitors cannot replicate.
Cross-account pattern detection, drift signals, mentorship-stall flags, network-density shifts. AI watches the whole portfolio so the Coordinator can focus on the accounts that need a human decision today.
Monthly leadership briefs, intervention suggestions, match recommendations, re-engagement scripts. Drafts only. The Coordinator edits, approves, or rejects every output before it leaves the Console.
Every message an employee receives is a human decision. Every match is human-approved. Every intervention is human-led. AI is the Coordinator's instrument, not the employee's interlocutor.
Productivity curve
3–5 accounts per Coordinator. Fully hands-on. Building the behavioral data.
6–10 accounts per Coordinator. Software handles signal detection, brief drafting, scheduling. Coordinator focuses on high-judgment intervention.
15+ accounts per Coordinator. AI surfaces predictive signals and personalized intervention recommendations. Coordinator remains the human face at every employee interaction.
The investment thesis is that this curve bends. Software makes each Coordinator dramatically more productive — and the data that makes it possible is captured while the work gets done.
Milestone
Stage
Complete first paid pilot engagements
Hire first full-time Culture Coordinator
Reach active accounts with engagement patterns we observe
Coordinator tooling reduces routine workload over time
First enterprise license agreement
Developing the Coordinator role takes time and domain knowledge. This is not a feature. It is an operational capability that compounds with every engagement.
Every engagement generates data on which rooms drive connection, which matching factors produce real relationships, and what signals predict disengagement. We are building a learning model in this space.
Most HR technology is built by people who have never held an HR role. Bridget has sat in the seat that approves these budgets and rolls out these platforms. That changes everything about how the product gets built.
The pre-seed period is structured to prove three things: that the Coordinator model produces measurable belonging outcomes, that the role is repeatable beyond the founder, and that the structured intervention dataset accumulates fast enough to anchor an AI moat at seed.
Pilot conversations are underway with prospective partners. Specific ARR targets, dataset volume thresholds, and customer counts will be informed by the outcomes of the first cohort and shared in direct investor conversations.
Hired and trained Coordinator #2, proving the role is repeatable beyond the founder.
Onboarded a senior technical lead with ML and full-stack expertise.
Built the structured intervention log infrastructure that anchors the AI moat.
Converted initial pilot relationships into paying customer commitments.
Established at least one named, public reference customer.
Detailed targets, financials, and use of funds shared with investors after an initial conversation.
Request the deck3 to 5 partners
Founder will serve as Coordinator for 3 to 5 paying pilot customers. Every engagement will be white-glove. Participation signals will be captured to inform the program. Goal: belonging score improvement, mentorship participation, and documented learnings to inform a future matching workflow.
Outcome: case studies, pricing validation, retention signals
10 to 15 customers
A goal of the cohort phase is to hire the first full-time Coordinator and develop software tooling that supports the routine work. The shape of that tooling will be determined by what Phase 1 engagement patterns teach us. We are not committing to a specific technical path today.
Outcome: repeatable role, gross margin proof, seed round readiness
Enterprise
Multi-Coordinator deployment for enterprise customers. Software handles routine work — matching, scheduling, signal aggregation, brief generation — so each Coordinator manages substantially more accounts. AI augments the Coordinator's judgment but never replaces the human relationship at the employee level. This depends entirely on what earlier phases teach us; we are not committing to a specific timeline today.
Outcome: healthy unit economics through Coordinator leverage, defensible category leadership
Most AI-first startups try to start at Wave 3 with no data. We are in Wave 1: capturing the structured intervention log that makes every later wave possible. The Coordinator generates the data while delivering value.
Structured intervention log. Rules flag stalled pairs and coverage gaps. Not ML yet, but it builds the dataset every later wave depends on.
Models predict stall risk and pair-fit on a dataset shape adjacent tools — intros (Donut), virtual events (Mystery, Confetti), ERG management (Chezie) — don't capture: every Coordinator intervention paired with its observed outcome. Triggered once volume supports it.
AI recommends interventions, drafts the monthly brief, augments judgment. Lets each Coordinator support more accounts.
Where AI sits in the product
AI is visible to the Coordinator only. Employees see a Coordinator reaching out. Keeping AI behind the human is intentional and durable.
Waves 2 and 3 are forward-looking aspirations, not current capabilities or commitments. Timelines depend on pilot velocity, data quality, and team capacity.
Founder & Culture Coordinator, CultureConnect
Bridget has spent her career in the HR seat that approves these budgets and rolls out these platforms. CultureConnect is built on that operator lens — what HR actually needs, not what software vendors assume.
Organizational Development & Fractional HR Consultant — current practice working alongside in-house HR teams
SHRM-CP (Society for Human Resource Management Certified Professional)
Trauma-Informed Coaching Certification · ICF ACC in progress
MA Organizational Psychology, expected Summer 2026
The questions that come up first. Direct answers, here.
Question
Today it looks more services-heavy. The investment is in the software and data layer that makes each Coordinator 3–5x more productive over time. Margins improve as software absorbs the routine work; the productivity curve and the milestone where margins cross 60% are walked through in direct investor conversations.
Question
It looks like software at scale. The software layer makes each Coordinator productive enough to support 15+ accounts at high margins, and the structured intervention data we capture creates a moat competitors cannot replicate.
Question
We're collecting a training set they can't access. By the time they try to copy us, our Coordinator network will be trained on three years of pattern recognition they don't have. And our Coordinators are trained OD consultants focused exclusively on relationships and connection — the science shows these are what increase well-being and performance.
A 30-minute conversation with Bridget to walk through the thesis, market timing, and what early traction looks like. No deck pressure.
If aligned, you get the full deck, financial model, pilot plan, and references from people who have worked with Bridget in HR operator roles.
SAFE-based pre-seed structure. Conversation-to-close timeline is short by design. We are building, not running a roadshow.
We are having focused conversations with aligned investors. Reach out directly and Bridget will respond personally.
Contact