The commercial mechanics. Pricing strategy (£50/seat evolving to seats + credits), pitch-pack pricing, the governance tier as procurement advantage, competitive positioning against presentation tools, general-purpose workspaces and platform bundling threats, enterprise procurement requirements, and go-to-market approach.
2.1 Baseline
2.1.1 Current price: £50/seat/month. Selling into pitch and concepting — highest urgency, most fragile context, fastest iteration need.
2.1.2 Second wedge: auditability and compliance of AI usage (brand/model constraints).
2.1.3 Two budget justification routes: pitch efficiency + win rate (new business budget, up to £200k/pitch), and governance/compliance risk (audit sheets of prompts, images, models).
2.2 Business Model Options
2.2.1 Option A — Seat-based SaaS (current). Simple mental model, forecastable MRR. Risk: AI costs are usage-driven, creates margin pressure. £50 is mid-to-high — defensible if positioned as Figma Org-tier (workflow + governance), not moodboarding. Anchors: Figma Org $55/mo, Enterprise $90/mo. Milanote $10-12/mo. Kive Basic $15/mo, Pro $75/mo.
2.2.2 Option B — Hybrid: seats + metered AI (recommended). Base seat fee + usage credits with generous included bundle. Aligns margin with inference costs. 3-4 plans with included credits and clear overages; enterprise gets pre-paid blocks and hard caps.
2.2.3 Option C — Project/pitch-based. Charge per "pitch project" or sell Pitch Packs. Fits agency mental model of pitch cost. Downside: harder to drive habitual adoption outside pitch moments.
2.2.4 Option D — Agency platform licence. Annual contract, minimum spend, unlimited/high-cap seats, admin + security bundle. Longer sales cycles, needs security posture. Best when governance is primary wedge.
2.2.5 Option E — Add-on revenue. Two natural add-ons:
- 2.2.5.1 AI Audit Pack — auto-generated reports of prompts, models, assets, approvals, rights
- 2.2.5.2 Creative Memory Layer — accumulated taste and decisions as premium retention feature
2.2.6 Caution: anything hinting at "training on your data" triggers procurement scrutiny. Must be opt-in with clear contractual controls.
2.3 Enterprise Procurement
2.3.1 Even indie agencies behave like enterprise when AI touches client work.
2.3.2 Must-haves for agencies handling brand/client data:
- 2.3.2.1 SOC 2 or ISO 27001 pathway; security questionnaire readiness
- 2.3.2.2 DPA, GDPR alignment, clear subprocessors list
- 2.3.2.3 "No training on customer data" default; clear retention/deletion
- 2.3.2.4 Audit logging, exportability, project-level access controls
- 2.3.2.5 Model/vendor governance: restrict models per client/project
- 2.3.2.6 SSO, SAML, SCIM (gated as enterprise features)
2.3.3 Governance can become a primary buying reason, not just a checkbox — especially as clients demand AI usage disclosure.
2.4 Competition
2.4.1 FC's claim: "workflow and context layer for ideation to pitch" — not raw generation.
2.4.2 Direct competitors:
- 2.4.2.1 Milanote — moodboarding, light structure, low price anchor
- 2.4.2.2 Kive — creative library + AI generation/search; blends asset management with AI
- 2.4.2.3 Miro / FigJam — strong collaboration, weak on pitch-ready packaging and governance
- 2.4.2.4 Notion / Coda — can approximate SoT, not native to creative references/production
2.4.3 Adjacent budget competitors: Pitch, Google Slides, Keynote, Figma Slides. AI deck generators: Gamma, Tome.
2.4.4 Production/generation platforms: Adobe (Firefly, Creative Cloud), Canva, Runway, Midjourney. May not own workflow, but can bundle it.
2.4.5 Platform threat: Google, Microsoft, Adobe integrating concepting into existing stacks. FC stays defensible as tool-agnostic workflow layer (browser extension + integrations) combined with creative memory and governance.
2.5 Ecosystem & Integration Partners
2.5.1 Key integration categories:
- 2.5.1.1 Daily workflow: Google Workspace, Microsoft 365, Slack, Teams, Drive, Dropbox, Asana, Jira
- 2.5.1.2 Creative stack: Figma, Frame.io, Runway, Adobe, Pinterest, Are.na, Bynder, Brandfolder
- 2.5.1.3 AI/model partners: OpenAI, Anthropic, Google — with policy controls per project
- 2.5.1.4 Channel partners: creative leaders, advisors, AI festivals, agency networks, production studios
2.6 KPIs
2.6.1 Activation: time-to-first-pitch-ready output, % projects with complete context, audit pack completeness, weekly active projects.
2.6.2 Retention & expansion: WAU/MAU per seat/agency, seats per agency + growth rate, project repeat rate, NPS (creatives + new biz leads).
2.6.3 Unit economics: gross margin by plan (incl. inference), AI cost per project/concept, CAC payback, sales cycle length + close rate by segment.
2.6.4 Outcome metrics: pitch cycle time reduction (baseline vs FC), pitch win-rate lift (self-reported initially), pitch cost avoided (hours, fewer external production cycles).
2.7 Go-to-Market Channels
2.7.1 Founder-led sales (primary). Warm intros via advisors + targeted outbound to indie agencies. Position by persona:
- 2.7.1.1 Creative leadership: "taste and judgment preserved, faster iteration"
- 2.7.1.2 New business: "more shots on goal per pitch budget"
- 2.7.1.3 Operations/risk: "audit trail and model governance"
2.7.2 Events and community. AI festivals, creative-thons with shared briefs, ECD/CCO judges, brand sponsors. Event outputs become case studies.
2.7.3 Product-led growth. Only when stability + cost controls exist. Free tier with hard usage caps to protect margin.
2.7.4 Integration-led acquisition. Browser extension = "works where you work." Publish integrations and templates. Co-marketing with Figma, Frame.io, DAM providers.
2.8 Recommendations
2.8.1 Keep £50/seat as list price. Introduce usage/credit layer behind the scenes to protect margin and prepare enterprise pricing.
2.8.2 Package "AI Audit Pack" (exportable report) as paid add-on or enterprise feature — unusually procurement-aligned for creative tools.
2.8.3 Create 2-3 buyer-specific one-pagers (Creative Lead, New Business, Ops/Risk) for consistent story.
2.8.4 Start tracking: time-to-pitch-ready, audit completeness, seat expansion per agency.