Operator-led turnarounds. Real outcomes.
Three SaaS companies. Three different constraints. One consistent playbook: find the real problem, put an operator on it, and rebuild the growth engine.
FlightDeck Systems
- Sector
- B2B SaaS · Operations
- Stage
- Series A
- Engagement
- 9-month engagement
Two consecutive years of negative growth. Lead volume looked healthy, but qualified pipeline was thin and churn was climbing quarter over quarter.
Constraint stack surfaced Product-Channel Fit as primary, with Retention & Expansion secondary. The team was investing in more of the wrong channels while the ICP had quietly drifted.
An embedded operator rebuilt the ICP, tore down and reassembled the demand engine, and installed a retention motion tied to expansion metrics.
- ARR growth−growth → +33% YoY
- Churndown 25% YoY
- ACVup 26%
- Lead quality~2x improvement
- Net new revenue2x+
Kumo
- Sector
- B2B SaaS · Vertical
- Stage
- Growth stage
- Engagement
- Multi-year Engagement
Strong acquisition, flat growth. Every dollar of new ARR was being offset by churn and stagnant customer value.
Dominant constraint: Retention & Expansion. Pricing was under-anchored; onboarding didn't drive time-to-value; expansion was accidental.
Repriced the product ladder, rebuilt onboarding around a single activation metric, and installed a customer success motion that pushed expansion into every quarter.
- NRR95% → 115%
- ARR growth75% → 140% YoY
- Avg. customer value$58 → $290/mo
- Base pricing$50 → $250/mo
- Logo retention89% → 94%
- Annual revenue churn12% → 6%
FlowSight
- Sector
- SaaS · Enterprise Workflow Intelligence
- Stage
- Pre-revenue, early GTM
- Engagement
- 12 months
A pre-revenue enterprise AI platform convinced its problem was Product-Channel Fit. Marketing, messaging, and demand generation were all firing, but lead volume stayed weak, sales cycles stalled, and prospects couldn't articulate the value or justify paying for it.
Dominant constraint: Product-Market Fit, not marketing. The product tried to solve too many workflows at once and was built for technical ambition rather than the risk tolerance of enterprise operations buyers, who wanted reliability, explainability, and low organizational risk over cutting-edge AI.
Helix replaced structured validation interviews with 100+ open-ended customer conversations across the ICP, then cut ~80% of the product surface to focus on the single capability buyers and users consistently valued most. Rebuilt around trust, explainability, and workflow fit.
- Product surfacereduced ~80%
- ICP conversations100+
- Customer trust & adoptionmaterially improved
- Willingness to paymaterially improved
- Next constraint surfacedEnterprise GTM motion