Sales copy
Ready-to-send proposals
Three versions aligned to ContractBot (contracts / legal SaaS), Risk layer (AI scan / analysis), and EUDI / trust infrastructure. Replace [Name] only—then send.
How to use
- ContractBot — mid-ticket (€20K–€50K): contract generator, legal SaaS, B2B tooling.
- Risk layer — fast-cycle (€22K–€48K): AI analysis, scoring, audit-style SaaS.
- EUDI / trust — high-ticket (€50K–€120K+): compliance, verification, enterprise.
Paste into any proposal
Self-healing infrastructure (controlled)
Adds €15K–€40K when reliability + audit evidence matter. Keep wording exact so buyers hear guardrails—not chaos.
I also design self-healing infrastructure layers — systems that detect degradation, stabilize automatically inside strict allow-lists, and log every action for audit and compliance.
Nothing changes pricing, legal text, or business rules without explicit flags and traceability — recovery is bounded to infra, retries, fallbacks, and safe degradation modes.
This is especially important for AI / fintech / legal SaaS where reliability and trust tie directly to revenue and enterprise readiness.
Paste into any proposal
Admin control plane (not “just dashboards”)
Adds €10K–€30K enterprise credibility. Separate from purely visual analytics UI.
I also build admin control planes, not dashboards only — tooling that lets you control revenue posture, identity & sessions, AI subsystem capacity, and production execution policy in real time, with audit-backed actions.
That pairing — visibility plus governed writes — is what separates a disposable SaaS from an infrastructure-grade product buyers recognize next to Stripe- or Plaid-class operators tooling.
Paste into diligence-heavy proposals
Revenue intelligence & investor dashboards (audit-ready)
Adds €12K–€35K. Positions beyond “analytics” — repeatable numbers for VC / lender conversations.
I deliver a Revenue Intelligence & Investor Dashboard Suite — investor, bank/risk, and operator views built on Stripe plus first-party funnel and usage telemetry.
Metrics (MRR, cohorts, LTV, leakage, refunds / chargebacks) are computed on a schedule, versioned with their definitions, and exposed through read-only roles, time-bound share links, and export/API outputs so diligence isn’t debating spreadsheet ghosts.
That transforms the product narrative from “we have dashboards” into transparent, investable revenue infrastructure — comparable to partner-grade reporting stacks.
Paste into billing / Stripe conversations
Post-Stripe Revenue Orchestration (not “Stripe setup”)
Explain three ladders: Billing Connect €3K–€7K · Revenue Engine €8K–€20K · Orchestration €20K–€50K+.
I don't just integrate Stripe — I build a post-payment revenue system. After checkout, your SaaS automatically:
- grants and revokes access from verified webhooks,
- moves users through subscriptions, upgrades, and downgrades,
- emits revenue events your team can reconcile,
- hooks retention experiments instead of leaking growth,
- and keeps traces your finance stack can defend.
Stripe creates the payment; the orchestration layer turns it into durable entitlement state, instrumentation, and growth loops.
Paste for enterprise procurement / tenders
DPA audit & compliance-as-infrastructure (€5K → €120K+)
Not “GDPR PDF packs” — lawful flows, DSAR tooling, verification page, audit trail in product.
I run a structured DPA Audit & Enterprise Compliance Integration programme tailored to SaaS stacks that must satisfy EU procurement: data-mapping workshops, DPAs tied to subprocessors actually in use, consent + DSAR execution paths, and an evidence-ready audit chronicle.
Where budget allows we ship the “wow” trajectory — public verification posture, AI processing guardrails aligned to DPIA narratives, billing/payload separation — so your platform reads as trusted infrastructure, not improvised compliance.
1 · ContractBot
When: contract generator · legal SaaS · B2B tool
Proposal — contracts / SaaS / B2B
Hi [Name],
What you’re building is not just a contract generator — it’s a decision system for businesses.
Right now, most tools in this space (including things like LegalZoom or Rocket Lawyer) stop at document generation.
👉 They don’t solve the real problem: risk + structure + usability.
What I see in your project
You want to:
- generate contracts
- support multiple scenarios / jurisdictions
- make it usable for real business workflows
👉 The gap I would address:
- no structured logic behind contracts
- no monetization layer
- no cross-border adaptability
How I would build it
I design systems like this as modular SaaS platforms, not templates.
Phase 1 — Architecture
- contract logic structure (clauses, conditions, variations)
- user flow (input → generation → output → reuse)
- monetization points
Phase 2 — Build
- dynamic contract generator
- structured clause system
- export (PDF / structured output)
- dashboard for reuse
Phase 3 — Revenue layer
- pricing tiers (per contract / subscription)
- paywall logic
- upsell (advanced clauses / cross-border modules)
Typical investment
👉 €20K – €50K depending on complexity
Why this approach works
You don’t just get “contract generator.” You get a scalable LegalTech product, ready for expansion (countries, modules, compliance).
Next step
If you share your target users, contract types, and current stage, I can map the architecture and give you a clear build plan.
2 · Risk layer
When: AI tool · document analysis · scoring / audit SaaS
Proposal — AI / scan / analysis
Hi [Name],
Your idea is strong — but right now it risks becoming just another AI tool.
👉 The real opportunity is to turn it into a revenue-generating system, not just analysis.
What I see
You want:
- AI analysis (documents / data)
- scoring / insights
- user-facing output
👉 The typical problem in these products:
- results are interesting, but not monetizable
- no clear upgrade path
- weak conversion at paywall
My approach
I build AI systems as decision + monetization engines.
Phase 1 — AI output design
- structured results (not just text)
- scoring logic
- explainable output
Phase 2 — Product flow
- preview → gated insights
- value escalation
- decision-driven UX
Phase 3 — Revenue architecture
- multi-tier paywall
- pricing based on value (not features)
- upsell from insight → action
Phase 4 — Retention
- user history
- repeat scans
- re-engagement triggers
Typical investment
👉 €22K – €48K
What you get
Not an AI feature — a product that converts users into paying customers.
Next step
Send me what you analyse, your target user, and current flow (if exists). I’ll show where revenue is currently lost and how to fix it.
3 · EUDI / Trust layer
When: compliance · fintech / identity · audit · enterprise SaaS
Proposal — Enterprise / compliance
Hi [Name],
This is not just a SaaS project — it’s a trust infrastructure system.
👉 Most teams approach this as development. The real challenge is architecture + compliance + verifiability.
What I see
You are building a system that produces results — but those results must be trusted externally.
👉 The risk:
- no audit layer
- no verification mechanism
- no compliance-ready structure
My approach
I design systems like this as multi-layer platforms:
Layer 1 — Core product
AI / logic / generation
Layer 2 — Audit
- structured output
- evidence-based reporting
- traceability
Layer 3 — Verification
- public verification endpoint
- verification UI (similar to Stripe / Plaid models)
Layer 4 — Compliance
- GDPR-ready data logic
- consent tracking
- audit-ready structure
Typical investment
👉 €50K – €120K+
What you get
Not just a SaaS — a platform that can be trusted, verified, and sold to enterprise clients.
Next step
If you’re serious about building this at a high level, I can map the full architecture and rollout plan.