Decision AI Platform

Enterprise Decision AI

Infrastructure

Continuous, Context-Aware, Cross-Functional.

#2
World Rank
Enterprise Reasoning
2.5×
Lift in Decision
Success Rate
$270M+
Decision
Capital Managed
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DecisionX Ontology Core — organizational reasoning infrastructure

Data sources: Documents, Databases, APIs, CRM, Meetings, Tickets

Data Ontology: Schema, Metrics, Lineage, Entities, Joins, KPIs, Source transforms

Domain Ontology: Processes, Dependencies, RCA Paths, Workflows, SOPs, Causal analysis

Decision Ontology: Goals, Tradeoffs, Policies, Context, OKRs, Guardrails

AI Agents: Finance Agent, HR Agent, GTM Agent, Ops Agent, Sales Agent, Risk Agent

Intelligence outputs: Signals, Reasoning, Reports, Decisions, Actions

Capabilities: Unified Cognition, Multi-Agent Reasoning, Enterprise Context

Documents
Databases
APIs
CRM
Meetings
Tickets

DecisionX

Ontology Core
Finance Agent
HR Agent
GTM Agent
Ops Agent
Sales Agent
Risk Agent
SignalsLive
ReasoningActive
Reports12 new
Decisions94%
ActionsAuto
Unified Cognition
Multi-Agent Reasoning
Enterprise Context

Powering 30,000+ Business Decisions

Trusted by Chiefs of Staff, Strategy teams, and GTM leaders

Recognized by NVIDIA as an AI-driven startup shaping the future of intelligent decision-making.

NVIDIA Partner

Before and After DecisionX

This is what measurably changes.

Four operational shifts. Each one measurable from day one.

Without DecisionX The Shift With DecisionX
6–8 months
6hrs
Ontology Setup
From months to hours
For Data Teams
Months of manual work. Done autonomously in hours.
Hallucinating generic AI
Zero
Hallucination
Grounded in your context
For AI and Analytics Teams
Every inference anchored to your data, not generic world knowledge.
20-day analyst sprint
30s
RCA & Forecasting
Decision workflows, not projects
For AI and Analytics Teams
20-day analyst projects. Now a 30-second decision workflow.
High analyst dependency
87%
Strategy Team Savings
Fewer bottlenecks, faster board prep
For Strategy Teams
Analyst dependency and coordination overhead — eliminated.
Without DecisionX
6–8 months
6hrs
Ontology Setup
From months to hours
For Data Teams
Months of manual work. Done autonomously in hours.
Without DecisionX
Hallucinating generic AI
Zero
Hallucination
Grounded in your context
For AI and Analytics Teams
Every inference anchored to your data, not generic world knowledge.
Without DecisionX
20-day analyst sprint
30s
RCA & Forecasting
Decision workflows, not projects
For AI and Analytics Teams
20-day analyst projects. Now a 30-second decision workflow.
Without DecisionX
High analyst dependency
87%
Strategy Team Savings
Fewer bottlenecks, faster board prep
For Strategy Teams
Analyst dependency and coordination overhead — eliminated.

From Data to Decisions

Go Live in 15 Days.

Agents do the work. Your team approves. No data engineering sprint required.

Day 0
Connect structured & unstructured data
Structured and unstructured sources, connected from day one.
Google Drive BigQuery HubSpot MS Teams Warehouse
Day 1
Data Ops Agents clean & unify
25 agents clean, structure and enrich data autonomously.
Messy files Metadata Lineage ETL ops Semantic joins
Day 10
Ontology Agents build the Causal State Graph
Data, Domain and Decision ontology built autonomously. Human approved before going live.
Built by Agents Human approved Data ontology Domain ontology Decision ontology
Day 15
Chat-based reasoning goes live
Cross-functional reasoning, signals and briefs grounded in your enterprise context.
Blindspot detection Foresight Reasoning Board briefs

Ontology Studio · State of Art · AI Teams

Three Ontologies.
One Causal State Graph.

Ontology Studio builds a living causal model of your enterprise across data, domain knowledge and decision history. Agents do the extraction. Your team governs what gets used.

01
Data Ontology

Metrics, schema and lineage

Agents extract source systems, metric definitions, schema and data lineage automatically. AI understands what gross_margin_pct means in your business, not just how to spell it.

MetricsSchemaLineageConventions
02
Domain Ontology

Industry rules and business logic

Import semantic models, brand hierarchies, channel structures and operating workflows. The context your business runs on, formalised and machine-readable.

BrandsChannelsWorkflowsRules
03
Decision Ontology

Goals, logic and decision history

Extract decision goals, reasoning logic, policies and outcome history from Slack, PDFs and AOPs. Decisions become institutional knowledge, not lost meeting notes.

GoalsPoliciesHistoryOutcomes
Built for reasoning, not just retrieval. The foundation that makes zero-hallucination AI possible and the reason DecisionX answers why, not just what.
Zero hallucination Why not what Causal AI
01

Data Ontology · Semantic Understanding

From raw data to meaning, automatically.

Agents extract what your data means, not just what it contains. Every metric, schema and business convention captured and structured automatically.

Metric inference Semantic enrichment Schema understanding Derived formulas
decisionx.ai · Semantic Layer
Semantic Understanding
02

A Causal State Graph for Enterprise

Data, Domain and Decision Ontology, unified.

DecisionX connects your data, domain and decision layers into a single graph, one that understands not just what is connected, but why things happen.

Causal edges State graph Decision memory Self-learning
decisionx.ai · Ontology Graph
Ontology Graph
03

Governed Enterprise AI, Human in the Loop

Built by Agents. Approved by Humans. Always.

Agents surface every conflict. Your team approves every resolution. Nothing changes the context layer without human sign-off.

Conflict resolution Human approval Governance Audit trail
decisionx.ai · Governance
Governed AI
Data Ops & Decision Memory

Autonomous Data Ops. Decisions That Compound.

DecisionX handles all data operations autonomously and turns every decision into reusable institutional knowledge that makes the next one sharper.

Metadata Agent
Schema Agent
Lineage Agent
Pipeline Agent
Semantic Join
Metadata Agent
Schema Agent
Lineage Agent
ETL Agent
Context Agent
Embedding Agent
Signal Agent
Inference Agent
ETL Agent
Context Agent
Embedding Agent
Metric Agent
Transform Agent
Semantic Layer
Governance Agent
Knowledge Agent
Metric Agent
Transform Agent
Semantic Layer
Data Ops Agents

Autonomous enterprise data operations.

25 agents handle all data plumbing autonomously: metadata, lineage, ETL and semantic joins.

Metadata extraction Schema inference Semantic joins Structured prep
Decision Object · Live Cycle
GoalIntent
ContextGrounding
ReasoningWhy
DecisionChoice
OutcomeResult
LearningUpdate
Every outcome updates the Causal State Graph
Decision Objects

Institutional intelligence that compounds over time.

Every decision tracked as an object. Goals, reasoning, outcomes, reusable institutional knowledge, not lost meeting notes.

Goal - Intent Reasoning - Why Decision - Choice Outcome - Result Learning - Update

Platform · Five Layers

Five capabilities. One continuous decision system.

Each layer maps directly to how leadership decisions actually happen — from raw data to governed action.

Always-on context Live signals Organisational reasoning
Foundation · Always OnLayer 01

Unified Context Layer

Connects all data sources into one continuously updated causal model. Every signal, every source, one coherent picture. Deploys in weeks, not months.

SnowflakeBigQuerySalesforceHubSpotSlackAPIs
Signals Agent
Synthesising live signals
Live
Scanning
Tier-2 return rate spike
Sales · Risk
Layer 2 · SignalsLayer 02

Internal Signals

Surfaces early indicators before they hit your KPIs. Detects what's changing, why it's changing, and what to do next — automatically, without a query.

Anomaly detectionRoot causeRisk flagsOpportunity signals
Foresight Agent
Scanning external signals
Live
Scraping public data
Competitor moves
Market · Competitive
Layer 3 · ForesightLayer 03

External Signals

Monitors public data for market shifts, competitive moves and regulatory changes — connected directly to your internal picture so context is never missing.

Competitor intelMarket signalsRegulatory shiftsPatent filings
Reasoning Engine
Scoring scenarios
Active
Processing
Attributing spend
Attribution · Forecast
Layer 4 · UnderstandLayer 04

Reasoning Engine

Ask any business question in plain language. Routes automatically to the right method — correlation, attribution, or forecasting — and explains its reasoning.

CorrelationAttributionForecastingRoot cause
Artifact Agent
Creating from conversation
Live
Creating
LTV/CAC breakdown slides
Chat to Slides
Layer 5 · DecideLayer 05

Boards and Reports

Every decision captured with full context and rationale. Board packs, slide decks, and live dashboards generated automatically from live data — no manual assembly.

Chat to SlidesChat to BoardsAuto board packsDecision log
Security & Governance

AI you can trust and defend.

Every decision DecisionX surfaces is explainable, traceable and auditable. Built from the ground up for enterprise governance, compliance and regulated environments.

Explainability

Every answer shows its working.

Three response layers summarised, deep dive and trail. Every answer is grounded in your data with full causal reasoning visible on demand.

Causal reasoning Deep dive Source attribution No black boxes
Specific Search-Term Actions by Recommendation
Most search terms still need more evidence, but the clearest immediate action is to scale a small set of proven exact-match tea terms and cut a narrow set of high-spend underperformers.
⚠
Data coverage note: 'impressions' exists in 3 tables with potentially different values. Suggested action: Specify which dimension/table to use.
⚠
Data coverage note: 'clicks' exists in 4 tables with potentially different values. Suggested action: Specify which dimension/table to use.
27Scale terms
62Negate / Reduce
5,009Test Further
68.7kAttributed sales
Key Findings
Only 27 of 5,098 rows are ready to scale classified as Test Further.
Strongest scale candidates:
Clearest cut cases:
Long tail of low-volume noise
Actionable Recommendations
Scale
Watch
Reduce
Analysis∧
12 Active Sources
Type in your question...
Traceability

Full trail on every response.

Every response carries a Trail tab source files used, the full reasoning chain, inferences made and the executed SQL. Nothing is a black box. Every step is logged and auditable.

Source files Reasoning chain Executed SQL Full audit log
Sources Used1 table · 5,098 rows
Sponsored_Brands_Search_term_report.xlsx
sponsored_brands_search_term_report5,098 rows
customer_search_termtargetingmatch_typecampaign_namead_group_nameimpressionsclicksspend_14_day_total_sales_14_day_total_orders
Reasoning Chain5 steps
1
Query classification DATA_TOOL
Query asks for specific data from structured sources
2
Table selection sponsored_brands_search_term_report
Table matched query intent based on schema metadata and column availability
3
Filter application 3 filters
CAST(date AS DATE) >= DATE '2024-05-03' CAST(date AS DATE) <= DATE '2026-05-03' customer_search_term IS NOT NULL
Filters derived from query constraints
4
Aggregation grouping
Grouped by: customer_search_term, targeting, match_type
5
SQL execution
Executed on 1 table · returned 5,098 rows
Inferences1
1
Selected columns with 'no suffix' suffix (audience segment) column_convention
Query Logic
Looks at Sponsored Brands search-term results May 2024–2026, totals performance per unique search phrase + targeting + match type, labels each as Scale / Negate/Reduce / Test Further, returns top 100 sorted by recommendation.
SELECT customer_search_term, targeting, match_type, campaign_name, ad_group_name, SUM(impressions) AS impressions, SUM(clicks) AS clicks, SUM(spend) AS spend, SUM(_14_day_total_sales) AS attributed_sales, 100.0 * SUM(spend) / NULLIF(SUM(_14_day_total_sales),0) AS acos_pct, CASE WHEN SUM(clicks) >= 25 AND SUM(_14_day_total_sales) >= 250 AND acos_pct <= 35 THEN 'Scale' WHEN SUM(clicks) >= 10 AND SUM(_14_day_total_sales) = 0 THEN 'Negate/Reduce' ELSE 'Test Further' END AS recommendation FROM sponsored_brands_search_term_report WHERE CAST(date AS DATE) BETWEEN '2024-05-03' AND '2026-05-03' GROUP BY 1,2,3,4,5 ORDER BY recommendation, attributed_sales DESC LIMIT 100;
Analysis∧
12 Active Sources
Type in your question...
EVALs

Continuous evaluation at ontology and query level.

Accuracy and grounding measured continuously at ontology and query level.

Ontology EVALs97%
Entity definitionsRelationshipsConventionsContinuous
Query EVALs94%
Factual groundingReasoning chainEvery queryDrift alerts
Periodic automated runsDrift alertsHuman review triggersScore history
Security & Compliance

Enterprise-grade. From day one.

Built for regulated enterprise environments.

SOC 2Type II
GDPRCompliant
ISO27001
RBAC, IAM and SSO
Public and private cloud deployment
Multi-LLM routing with governance
Full audit trail on every query

Decision intelligence platform

Build the enterprise
context layer for
decision AI.

See how DecisionX turns enterprise data, ontology, reasoning and agents into a continuously learning decision system for strategy and analytics teams.

Book a demo