01
Attribution signals
Spend, conversion depth, overlap, and contribution change.
Enterprise AI, data, and workflow systems
Turn fragmented data into measurable decisions
EPVANTA turns attribution data into a real-time advertising decision model for audience adjustment, budget control, and self-evolving media execution.
Selected partners
Built to work alongside the cloud, media, and platform systems enterprise teams already rely on.
Cloud infrastructure
Enterprise cloud
Media measurement
Performance channels
Live decision model
Open attribution signals into live media moves.
EPVANTA keeps attribution data open during execution, so teams can adjust audiences, control budget, and evolve bidding logic before inefficiency spreads.
Fund efficiency
+60%
Target uplift when decisions respond to live attribution signals instead of delayed reporting loops.
Operating focus
Audience adjustment
Budget control
Self-evolving learning
A simpler operating surface that explains what changed, what to move next, and why the capital trade-off is justified.
Decision flow
One open loop from signal intake to capital efficiency.
Instead of stacking explanations, the model is organized as a readable operating path: inputs stay open, decisions stay interpretable, and actions stay accountable.
02
Audience model
Reweight segments that deserve more reach and budget.
03
Budget engine
Use CAC, ROAS, and thresholds to decide the next move.
04
Media execution
Update bids, pacing, and channel weight toward stronger efficiency.
Audience and budget
Adjust targeting and spend while campaigns are still live.
Move from passive review to live reallocation by showing which audiences deserve more pressure, which channels should slow down, and where spend efficiency begins to weaken.
Audience reweighting
Shift exposure toward cohorts still compounding value
See which cohorts still deserve pressure and reduce waste before broad audiences consume the budget.
Self-evolving logic
Let the model learn from indicator drift, not just delayed reports
Each loop improves recommendation quality by learning from changing attribution patterns, so operators can act with more confidence and less reporting delay.
Core demo
Experience a live attribution simulation
Adjust spend, clicks, conversions, revenue, and attribution model to see how channel contribution shifts in real time.
Input assumptions
Adjust your campaign mix
Google Ads
Meta Ads
TikTok Ads
Total Spend
$27,000
Total Revenue
$115,600
Overall ROAS
4.28
Overall CAC
64.4
Output view
Performance summary and attribution view
Channel summary
ChannelSpendConversionsCACROAS
Google Ads
$12,000164.373.04.37Meta Ads
$9,000147.561.04.64TikTok Ads
$6,000107.355.93.57Insight summary
Multi-touch attribution suggests Google Ads and Meta Ads jointly shape most conversion influence. TikTok Ads contributes strongly to discovery through upper-funnel traffic signals, while Meta Ads currently shows the strongest direct efficiency in ROAS terms.
Tip: change the model, disable a channel, or shift conversion inputs to see how attribution weight and CAC respond immediately.
Why EPVANTA
Enterprise results before technical noise
Each capability is framed around the commercial and operational outcomes enterprise teams actually care about.
Value proposition
Adjust audience targeting from live attribution signals
Continuously rebalance audience focus as contribution quality, conversion depth, and channel overlap begin to shift.
For teams optimizing creative, segment, and platform mix while campaigns are still running.
Value proposition
Control budget with decision-ready efficiency thresholds
Turn spend, CAC, ROAS, and contribution signals into faster budget moves instead of delayed reporting reviews.
For leaders who need to defend reallocation decisions with clearer performance logic.
Value proposition
Let bidding logic learn from evolving media behavior
Use self-evolving indicator patterns to surface where bids, pacing, and channel weighting should adapt next.
For operators who want media execution to improve as new attribution evidence accumulates.
Value proposition
Make capital efficiency visible at the operating layer
Frame every optimization loop around a target of up to 60% stronger fund efficiency across active campaigns.
For organizations that need growth velocity and financial discipline to improve together.
Solutions preview
One decision model, three execution paths
Move from top-level positioning into the solution track that best matches your buying context.
Investment
Starting from US$19,980
AI Ads Attribution
Unified attribution visibility for teams operating across multiple ad platforms, with a clearer view beyond last-click reporting.
Growth teams, marketing leads, analytics teams
A structured dashboard that clarifies contribution and efficiency
Investment
Starting from US$43,000
SaaS ERP Custom Development
Build systems around your business instead of forcing your teams into rigid software patterns.
Operations leaders, finance and process-heavy organizations
Modular business workflows with role-based control and reporting
Investment
Custom scoping available
Enterprise Agent
Put AI to work inside real operational processes through internal assistants, workflow agents, and knowledge automation.
Internal support teams, operations teams, knowledge-heavy organizations
Role-aware agents grounded in real processes and approved knowledge
Platform logic
Three layers, one enterprise operating model
The platform narrative is intentionally simple: data inputs, intelligence logic, and usable application surfaces.
01
Data Layer
Ad platform inputs, CRM or ERP records, and structured or unstructured internal business data.
02
Intelligence Layer
Attribution logic, workflow orchestration, AI reasoning, and process automation rules.
03
Application Layer
Dashboards, decision support interfaces, internal tools, and operational agent experiences.
Use cases
Built for high-friction operational contexts
EPVANTA is most effective where fragmented data, process complexity, or internal routing creates drag on business decisions.
Growth teams
Audience targeting and budget pacing often lag behind what attribution data is already showing.
Use one live decision model to rebalance audience groups, channel pressure, and spend windows in real time.
Faster budget moves with clearer proof of why each shift matters.
Media operators
Bid and pacing decisions are still made through siloed dashboards and delayed human interpretation.
Surface the next optimization action from attribution-weighted efficiency and learning signals.
More stable execution with less manual guesswork between reporting cycles.
Revenue leaders
Management needs stronger confidence that paid growth is using capital efficiently.
Connect spend logic to contribution quality, efficiency thresholds, and scenario-based reallocation rules.
A clearer path toward up to 60% stronger fund efficiency.
Agency teams
Clients expect optimization logic they can understand, not just post-campaign commentary.
Turn attribution evidence into a live decision layer for targeting, budget control, and model-backed recommendations.
Sharper client trust and more persuasive decision narratives.
Cross-market teams
Regional channels drift apart when each team optimizes against different indicators.
Standardize the optimization model while still adapting audience and spend logic to local signals.
Tighter governance with more adaptive execution across markets.
Developer preview
Built for live optimization logic and structured integration
Connect attribution APIs, event ingestion, learning signals, and outbound workflows into a real-time decision layer for media execution.
Event ingestion
Structured channel-level inputs with reporting-aware schema design.
Webhook support
Async updates for connected systems and notification workflows.
Access governance
Managed credentials and enterprise-aware access control structures.
Bilingual delivery
Content, navigation, legal links, and demo labels stay aligned across EN and 中文.
Conversion path
See how a live decision model improves spend quality
Explore a tailored demo built around your audience logic, budget controls, and the operational path to up to 60% stronger fund efficiency.
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