Unlock AI‑Driven Business Insights
Transform raw data into actionable predictions in under 60 seconds, with enterprise‑grade scaling, multilingual narratives, and rock‑solid security.
Get Started View Documentation
Transform raw data into actionable predictions in under 60 seconds, with enterprise‑grade scaling, multilingual narratives, and rock‑solid security.
Get Started View DocumentationIngest raw transactions, sensor feeds or free‑text; deliver predictions via plug‑and‑play microservices in < 60 s.
Go live with your first campaign in ≤ 2 hours. Typical 6–14 % EBIT uplift within 3 months.
Automatic GPU routing with seamless CPU fallback—no DevOps gymnastics required.
First projects live in ≤ 2 hours; instant ROI tracking.
Automatic routing to GPUs or safe CPU mode.
English, Spanish & Portuguese out‑of‑the‑box, more coming.
TLS 1.2+, SOC 2 Type 2 audit, ISO 27001‑certified data centers.
Real‑time queue & worker stats, usage & billing APIs.
Canary deploys, semantic versioning (/v1), backward compatibility.
POST JSON to /api/v1/ai/{route} with your credentials.
Your task is queued & processed by queue and orchestrator.
Horizontal autoscaling on Kubernetes
Poll /taskadmin/tasks/{id} and download JSON payload.
Automatic cluster analysis, persona cards, and narrative decks.
Short‑ and long‑term revenue & units forecasting with promotions.
Per‑customer churn probabilities & recommended retention actions.
Executive summaries, slide copy, and creative briefs via JSON.
By leveraging AI‑driven segmentation (endpoints like purchasing_segmentation and segmentation_report), enterprises can achieve up to a 300% increase in marketing ROI, enabling ultra‑precise campaign targeting and measurable brand lift.
Moreover, 77% of marketers report that AI‑based customer segmentation is critical for delivering personalized experiences that drive higher customer lifetime value and lower acquisition costs.
In practice, a national online retailer cut customer acquisition cost by 22% and boosted repeat purchases by 18% within three months—translating to over $1.5 M incremental revenue in the first year.
Fluxrails recommendation APIs (e.g. propensity_buy_product, recommend_user_items) can deliver up to a 30% lift in total sales by surfacing high‑propensity offers, while boosting customer satisfaction by 25% through hyper‑relevant suggestions.
Advanced routes like uplift_model and dynamic_pricing_recommend have driven 10–50% increases in average order value in live A/B tests across multiple retailers.
For example, a specialty retailer saw its AOV rise from $75 to $96 (+28%) and its conversion rate climb by 12% within one quarter of integrating Fluxrails personalized recommendations.
With forecasting endpoints (e.g. forecast_revenue, forecast_units_asyncio), companies have boosted forecast accuracy from 67% to 91% at the SKU/location/day level, slashing manual effort by 85% and refocusing analysts on high‑value strategy.
These accuracy gains translated into a 2.8 pp increase in gross margin and delivered a 342% ROI within the first year.
In another case, a mid‑market retailer reduced excess inventory by 15% and stockouts by 10% over six months—freeing up $1.8 M in working capital and cutting markdown losses by $500 K.
Fluxrails supply‑chain modules (like inventory_optimization and excess_inventory_nlp) have cut excess inventory by 31% and stockouts by 72%, boosting on‑shelf availability and avoiding $2.3 M in annual markdowns.
Similarly, a proof‑of‑concept in a large retail chain saw a 15% reduction in inventory overhang and a 10% drop in stockouts within six months, releasing $1.8 M in tied‑up capital for reinvestment.
Fluxrails risk‑analysis endpoints (credit_risk_score, churn_risk) have expanded credit approvals by 27–30% while reducing default rates by 15–16%, lowering provisioning costs and unlocking new credit segments.
AI‑powered churn models cut customer attrition by 22%, preserving $2.8 M in annual recurring revenue.
Automated anomaly detection (anomaly_transactions) flags suspicious activity 3× faster, reducing fraud losses by 40% and saving $1.1 M in operational costs through early intervention.
purchasing_segmentation: Cluster & persona discovery for targeted campaigns.segmentation_report: KPI & narrative pack for executive summaries.segment_hierarchy_chart: Dendrogram data for interactive cluster exploration.segment_subsegment_explore: Drill into clusters & sub‑clusters for fine‑grained insights.segment_cluster_profiles: Detailed feature profiles per segment for playbook creation.customer_segmentation: Custom segmentation to fit bespoke business rules.customer_features: Generate clean feature vectors for downstream ML or dashboards.customer_loyalty: Compute loyalty indices & bucket tiers for retention programs.customer_rfm: Classic R F M scoring & tiering to trigger lifecycle actions.customer_clv_features: Prepare BG/NBD + Gamma‐Gamma model inputs for CLV.customer_clv_forecast: Predict 6/12/36 mo CLV with confidence bands & tiers.churn_risk: Estimate churn probability & recommend retention offers.nps: Analyze Net Promoter Score for customer satisfaction tracking.churn_label: Flag customers as “at‑risk” for automated workflows.propensity_buy_product: Score likelihood to purchase specific SKUs for targeting.propensity_respond_campaign: Predict campaign response to optimize spend.propensity_upgrade_plan: Estimate upgrade propensity for upsell strategies.recommend_user_items: Personalized item recommendations to boost AOV.recommend_similar_items: Suggest alternatives to increase cross‑sell.cross_sell_matrix: Generate cross‑sell affinity scores for bundling.upsell_suggestions: Identify high‑margin upsell opportunities.dynamic_pricing_recommend: Price optimization recommendations for revenue lift.uplift_model: Quantify incremental lift from marketing treatments.forecast_revenue: Revenue trend forecasting for budgeting.forecast_units: Unit‑sales forecasts to drive procurement.forecast_units_asyncio: Async batch unit forecasts for large catalogs.forecast_cost: Cost forecasting for margin analysis.forecast_cost_improved: Enhanced cost forecasts with seasonality.forecast_cost_totus: Total cost & overhead forecasting.inventory_history_improved: Historical inventory analytics.inventory_optimization: Stock-level optimization to reduce costs.nlp_openai_excess_inventory_report: Narrative excess‑stock insights.excess_inventory_nlp: NLP‑driven overstock analysis.nlp_analisys: Free‑text anomaly detection in supply logs.nlp_analisys_en: English‑only supply‑chain NLP insights.credit_risk_score: Customer credit‑risk scoring.credit_risk_explain: Explain credit‑risk drivers.channel_attribution: Revenue attribution across channels.journey_markov: Markov‑chain customer journey modeling.journey_sequences: Sequence analysis of touchpoints.anomaly_transactions: Transaction anomaly detection.anomaly_accounts: Suspicious account‑activity alerts.anomaly_graph: Graph‑based network anomaly detection.sentiment_report: Batch sentiment‑analysis reports.sentiment_realtime: Real‑time sentiment monitoring.Auto‑cluster your customer base by spending, frequency, diversity and loyalty; returns labels, centroids & persona summaries.
Use for targeted campaign audiences & multi‑channel persona segmentation.Generate a full narrative report (JSON) with executive summary, KPI tables and slide‑ready copy in EN/ES/PT.
Perfect for automated BI dashboards & stakeholder updates.Convert raw dendrogram output into D3‑ready nodes & links for interactive tree or radial charts.
Ideal for drill‑down explorer UIs with zero front‑end parsing.Score each customer’s likelihood to purchase specific SKUs; returns normalized probabilities.
Boost ad‑targeting ROI by focusing on high‑propensity segments.Personalized product recommendations based on user history and similarity to peers.
Increase average order value with tailored cross‑sells.Suggest optimal price adjustments to maximize revenue uplifts per item.
Automate margin‑focused pricing strategies.Time‑series projection of revenue over a 1–60 month horizon with confidence intervals.
Use for budgeting, financial modeling & board reporting.Asynchronous batch API for large‑scale unit forecasts across thousands of SKUs.
Ideal for retail catalogs with real‑time inventory planning.Compute optimal stock levels by SKU to minimize holding costs and stockouts.
Shrink working capital and improve fill‑rates.Generate a narrative report on aging stock, bottlenecks, and suggested clearance actions.
Turn raw supply‑chain data into actionable insights.Evaluate customer creditworthiness in real‑time using behavioural and financial inputs.
Protect receivables and set automated credit limits.Detect unusual transaction patterns with graph and statistical methods; flag suspicious activity.
Automate fraud alerts and compliance monitoring.