01
Business mapping
Targets (revenue, pipeline, tender win-rate, contract risk), data sources, decision gates, compliance constraints.
Consulting · AI revenue & risk infrastructure
We don’t build models.
We build systems that predict and steer revenue.
Predictive Decision Layer: lead & deal scoring, tender/bid prioritisation, contract-risk signals — tied to funnel routing, experimentation, CRM/contract integrations, and a feedback loop measured in money.
You don’t need another undifferentiated model — you need a system that forecasts what converts, escalates consulting lanes, exposes risk ahead of signatures, and loops prediction vs actual cash automatically.
- Estimate deal probability and revenue uplift before pipelines stall.
- Flag high-intent prospects worth €5K+ consulting vs self-serve lanes.
- Route actions (pricing, tenders, escalation) aligned with contracts — not slideware.
Grounded posture: deterministic, explainable scoring first (audit-friendly), gated experimentation (bandits/A-B hooks), reinforcement from payment events — aligned with GDPR/EU diligence expectations.
What you actually get
Five sequenced workstreams — each ends in something your board can defend: revenue impact, risk reduction, or procurement-grade evidence.
02
Explainable scoring
Feature design, intent & value models, risk flags — no black-box theatre; documentation for legal & finance reviewers.
03
Integration layer
Site routing, bandit hooks, CRM/forms, contract repositories, secure worker APIs + event logging.
04
Decision automation
SaaS vs consulting lane selection, high-value alerts, tender triage, release/hold guardrails before signature.
05
Validation & feedback
Prediction vs payment reality, rolling accuracy, refresh cadence, change control when models shift — so AI isn’t a one-off PDF.
Use cases we ship
SaaS growth
Who converts vs needs a demo — pricing vs trial vs CS escalation based on score + payment priors.
Consulting pipeline
Identify €5K–€50K conversations early; assign partner time where lift is highest.
Tenders & bids
Win-probability + resource cost signal before you burn partner weeks on low-fit RFPs.
Contracts & compliance
Clause-level risk heatmaps tied to revenue dependencies (not generic “redline AI”).
Why this is different
- Not ML research monthlies — production guardrails, revenue-weighted learning, explainability by design.
- Not another BI skin — decisions wired into routing, contracts, CRM, and cash events.
- Not generic “AI agents” — outcomes measured in ARR, win-rate, risk avoided, partner hours saved.
This is the same architectural discipline we use on ContractBot-class stacks: worker APIs, event trails, deterministic scoring overlays, gated experimentation.
Packages
Sized for procurement reality — milestone-based statements of work available on request.
Starter
Predictive Setup
€2,500 – €4,000
- Single prediction lane (lead score or churn proxy)
- Explainable baseline model + documentation packet
- Light integration (CSV export, webhook, or site hook)
Core
Predictive System
€5,000 – €9,000
- Intent + revenue potential stack
- Funnel routing + guarded experimentation hooks
- Event contracts + KV logging patterns
Enterprise
AI Decision Infrastructure
€12,000 – €25,000+
- Multi-objective models across revenue, tenders, clauses
- Deep ContractBot/workflow integrations
- Continuous optimisation loops + SOC-style controls
Retainer tuning
€500 – €2,000 / month
Rolling feature refresh, KPI alignment, experimentation review, infra drift audits.