Decision AI · Strategy & Analytics Teams

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Clarity & Context.

Full Confidence.

The Full Picture.

Clarity & Context.

Surface blindspots.
Reason cross-function. Build foresight.

Not a dashboard. Not a copilot. A decision system.

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DecisionX · Signals

Live

Daily · 2:25 pm

Critical

Is velocity of SKU launches tracking with revenue density per SKU over time?

Only 2 of 15 months had any launches...

Needs Attention

Is velocity of SKU launches tracking with revenue density per SKU over time?

Only 2 of 15 months had any launches...

Needs Attention

Where is there misalignment between marketing's channel mix and finance's margin targets?

D2C receives 53.3% of spend but only 38.8% of margin...

Chat

Where is there misalignment between marketing's channel mix and finance's margin targets?

Marketing vs Finance Channel Alignment

+14.5

D2C Gap

−14.9

Mktplace Gap

+0.4

Offline Gap

Analysis

D2C over-invested — 53.3% spend, 38.8% margin contribution

Marketplace under-invested — 31.2% spend, 46.1% margin

Re-balance toward Marketplace to align with finance targets

Thinking · 13 steps

Thought for 13 steps

Retrieved — 6 records in 326ms

Thinking — Processing cohort retention curves...

Synthesizing — Structuring LTV/CAC channel narrative...

Exploring — Identifying highest LTV-to-CAC channels...

Summarised

Deep dive

Trail

LTV-to-CAC by Acquisition Channel (Jul–Sep 2024)

Nykaa Ads delivers the highest LTV-to-CAC (51.7x) at the lowest CAC (₹27.76). Google lags at 21.9x. Shift spend toward Nykaa Ads and Meta; review Google and Amazon for efficiency.

Headline KPIs · Q3 2024

Nykaa Ads — 51.73x

Top LTV-to-CAC

₹27.76 (Nykaa)

Lowest CAC

₹1,588 (Influencer)

Highest 12M LTV

45.72x — Meta

Strong LTV-to-CAC

Google — 21.95x

Weakest LTV-to-CAC

30.52x — Amazon

Amazon Ads

LTV-to-CAC ratio by channel

Nykaa Ads

51.7x

Meta

45.7x

Amazon Ads

30.5x

Influencer

—

Google

21.9x

Recommendations

For Nykaa Ads

Increase budget in a controlled way — prioritise incremental scaling while monitoring CAC stays near ₹27.76

Protect quality: verify expansion does not dilute 12-month LTV performance

For Google & Amazon

Put under efficiency review before adding spend

Focus on lowering CAC through targeting and landing page conversion improvements

Analysis

Internal Data

Thinking

6 Active Sources

Fix marketplace returns before rivals win the coffee-care shelf

Next 6 monthsConvergence

Summary

Detailed

Key Assumptions

Returns >12% correlate with ranking decline — causally important enough to guide intervention.Pending

A meaningful share of demand is won or lost on marketplaces where search rank drives conversion.Pending

Competitors with broader marketplace presence can absorb demand when listings weaken.Pending

Evidence

Medium (60%)

External market observations

High (80%)

Internal dataset signals

WOW Skin Science has broad scrub/kit assortment visibility on Amazon India, competing for the same marketplace occasions as mCaffeine.

Medium 60%

SKUs with >12% marketplace return rates correlate with ranking decline within −45 days — high commercial risk signal.

High 80%

✦ Key Takeaways

Prioritise causal impact of marketplace returns on ranking decline.

WOW Skin Science is the clearest marketplace competitor — monitor Amazon rankings.

Post-purchase retention, not acquisition, is the primary lever.

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.

For Strategy Teams

The decisions that defineYour Year

Consumer brand strategy teams don't lack data. They lack a way to turn competing signals into one clear, defensible call.

Chief of staff and Revenue

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Investment

Where should we put the money?

Which brands, SKUs, or categories get backed this cycle. At a consumer brand this decision touches Marketing, Sales, Trade, and Finance simultaneously, it breaks without cross-functional reasoning. DecisionX aligns every function on the same call.

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Chief of staff and sales

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Performance

Why is performance diverging from plan?

Strategy teams are always asked to explain gaps between forecast and actuals, between what Sales promised and what Marketing delivered. DecisionX surfaces the signal before someone else escalates it to the board.

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chief of staff and marketing

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Growth

Where do we grow next?

Which geographies, retail partners, and consumer segments are primed and which look attractive but carry hidden risk. The most recurring high-stakes call a consumer brand strategy team owns. It's visible to the CEO, contested across functions, and always under time pressure.

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Each of these decisions required the same thing. Multi Layered Cross functional reasoning.

Your dashboards tell you what is happening. DecisionX tells you why - and what to do next. Five reasoning engines work across Sales, Marketing, Operations and Finance simultaneously - so the answer reflects the full picture, not just the function closest to the problem.

Correlation hover events

Correlation

Finds the relationship between signals across functions - the pattern that only becomes visible when all four are read together.

Attribution hover segments

Attribution

Identifies what is actually driving an outcome - the real cause, not the assumed one each function defaults to.

Root Cause hover nodes

Root Cause Analysis

Goes beyond the surface signal to find where the problem originated - and which function, decision, or assumption introduced it.

Forecast hover months

Forecasting

Projects what happens next under each option - grounded in live cross-functional data, not a single function's assumptions about the rest.

For Analytics Teams

Make AI work at Enterprise grade

Zero hallucination. 100% grounded in your organisational context built from your data up, not from generic world knowledge.

Make Data

01 - DATA OPS AGENTS

From raw data to meaning automatically

Data Ops Agents ingest your sources and extract metrics, conventions, and decision context automatically. DecisionX knows what gross_margin_pct means in your business not just how to spell it.

20 metrics detected

63 conventions

Derived formulas

Schema inference

Ontology Graph

02 — ONTOLOGY AGENTS

A state graph built from your data, ground up

Ontology Agents extract decision ontology from your unstructured data and import domain semantics you've already built. The result: AI that reasons from your reality causally connected, semantically grounded.

State graph

Causal connections

Unstructured extraction

Domain import

Conflicts

03 — HUMAN IN THE LOOP

Resolve conflicts conversationally. Never lose control.

Ambiguities and contradictions surface for your review never silently resolved. Just tell DecisionX what you mean. It proposes the fix, you approve it. A prescriptive, structured way to build your ontology with your team in the loop at every step.

Conflict detection

Proposed fixes

Chat to resolve

Merge & approve

Building blocks

Five Capabilities.
‍One continuous decision system.

Each building block maps directly to a layer of how leadership decisions actually happen.

Data Knowledge Graph

Snowflake

BigQuery

Slack

Salesforce

HubSpot

Jira

Notion

Stripe

Shopify

Google Ads

Meta Ads

Looker

Foundation - always on

Unified Context Layer

Connects Sales, Marketing, Operations and Finance into one continuously updated model of your business. What takes 8–12 months to build in-house, DecisionX deploys in weeks.

Live sync

Self-learning

Compounding intelligence

Deploy in weeks

DecisionX — Signals Agent

Signals Agent

Synthesising live signals

Live

Scanning

Google ROAS analysis

CoS · Risk

Layer 2 - Sense

Internal Signals

Surfaces early indicators of problems developing inside the business - before they hit KPIs, before they reach the board. Every signal delivers three things: What is happening, Why it is happening, and the Next Best Action.

Urgent · Watch · Positive

What / Why / Next action

Cross-functional detection

DecisionX — Foresight Agent

Public Data

Competitor moves

Market signals

Regulatory shifts

Macro indicators

Trade data

Govt policy

Patent filings

Funding signals

Sentiment data

Job signals

Pricing intel

Foresight Agent

Scanning external signals

Live

Scraping public data

Competitor moves

Market · Competitive

Layer 3 - Foresight

External Signals

Continuously monitors public data for market shifts, competitive moves, regulatory changes and macro signals - then connects them to your internal picture. Your internal signals are never read in isolation from the world they operate in.

Competitive moves

Market shifts

Regulatory signals

Watchlist

DecisionX — Reasoning Engine

Reasoning Engine

Initialising

Reasoning

Layer 4 - Understand

Reasoning

Ask any business question in plain language. The platform routes it to the right analytical engine automatically - correlation, attribution, or forecasting - and returns an answer grounded in your live data. You never choose the method. You only ask the question.

Live sync

Self-learning

Compounding intelligence

Deploy in weeks

DecisionX vs LLM

Compare decision reasoning - DecisionX vs LLM Ask the same business question. See the difference in context, reasoning and action.

Try it yourself →

DecisionX — Artifact Agent

Artifact Agent

Creating from conversation

Live

Creating

Q3 channel deck

Chat to Slides

Chat to Slides

Output

Layer 5 - Decide

Boards & Reports

Every decision captured with its context, rationale, and scenarios considered. Board packs generated automatically from live data. Nothing evaporates after the meeting. The full audit trail is one click away - six months later.

Auto board packs

Decision records

Shared scenarios

Explainability

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Why DecisionX

The things that are
genuinely hard to replicate.

01

Faster to value than building in-house

A unified context layer across four functional data sources takes internal teams 8–12 months to build. DecisionX deploys in weeks - with integration, data modelling and learning already done.

02

Compounding intelligence

The platform learns from every data update and every conversation. The longer you use it, the more accurate its signals and the sharper its reasoning. Intelligence compounds - it doesn't decay.

03

Always live - never a snapshot

Every number on every screen is live. Not yesterday's export, not last week's report. When you ask a question, the answer is grounded in what is actually happening right now.

04

Explainability built in

Every reasoning output shows its sources and logic. Every decision retains the evidence that informed it. Auditability is structural in DecisionX - not an afterthought bolted on for compliance.

05

Complementary to LLMs you already use

DecisionX sits above Claude, GPT and Gemini as a business context layer. It makes LLMs useful for your specific business by grounding their reasoning in your actual live data.

06

Cross-functional by design

Most platforms are single-function with cross-functional claims bolted on. DecisionX is architected around the cross-functional question from day one — the only kind of question that matters at the CSO level.

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Stop assembling the picture. Start deciding from it.

See DecisionX running on your business - with your data, your functions, your questions. Most teams are live within weeks.

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