Product
How Advisor works, end-to-end. The capabilities, the architecture, and the integration model.
Capabilities
Four capabilities, one platform.
Advisor combines a conversational interface for new questions with structured workflows for forecasting, optimization, and reporting. All four work against the same data, the same business knowledge, and the same audit trail.
Capability 01
Ask any business question. Get a recommendation, not a report.
Type the question a board member asked, or the one your CFO raised in the ExCom. Advisor works through the analysis: data pulled, assumptions stated, scenarios compared. It returns a structured recommendation with its reasoning visible.
Every output is grounded in your actual data, with sources cited at every step. Ask isn’t a chatbot stitched onto a dashboard. It’s a reasoning interface that runs the same analytical engines used by Forecast, Optimize, and Report, with the natural-language layer on top.
What it handles
- New questions that fall outside the planning cadence
- Variance investigation across multiple dimensions
- Cross-system queries that would normally require multiple analyst hand-offs
- Slide-ready outputs with title, chart, insights, and recommendation in one response
Capability 02
Test a decision before you make it.
Change a price, a volume, a headcount, a capex assumption. See the impact across P&L, cash flow, and balance sheet, modeled against the same driver-tree decomposition your FP&A team would build manually.
Run three scenarios side by side. Save them, share them, return to them when the inputs change. The methodology is rule-based and transparent, so finance leadership can challenge any assumption and recalculate without rebuilding the model.
What it handles
- Rolling forecasts with version control
- Scenario modeling against interdependent assumptions
- Driver-tree decomposition to operational variables
- Variance bridges between forecast and actuals
Capability 03
Find the savings, sized and prioritized.
Advisor scans operations, spend, and contracts, then proposes specific actions ranked by financial impact. Each recommendation comes with a transparent business case: the data behind the savings estimate, the assumptions, the implementation difficulty, and the impact range.
You approve, adjust, or reject. The platform tracks initiative progress against the original case, so the savings story is auditable from identification through realization.
What it handles
- Spend analytics with maverick spend and price leakage detection
- Should-cost analysis with bill-of-materials modeling
- Initiative pipeline with sizing, prioritization, and tracking
- Category-level savings opportunity identification
Capability 04
Performance summaries that update themselves.
Variance bridges, narrative explanations, and performance summaries that pull from live data and update automatically. Templates are flexible. Outputs are pixel-perfect, slide-ready, and consistent across reporting cycles.
Your FP&A team stops assembling slides. They start advising the business.
What it handles
- Automated month-end and quarter-end reporting
- Variance explanations with root-cause attribution
- Board-ready presentation outputs
- Cross-entity consolidation with consistent definitions
How it works
Built differently from the AI tools you've been pitched.
Most AI products in the enterprise space are LLM wrappers around dashboards. Advisor is built differently, because the work it does demands a different architecture.
Mechanic 01 · Architecture
Every AI product claims to be intelligent. Here's how Advisor actually works.
Advisor is not an LLM wrapper. It's a hybrid system where each output type has a specific composition, deterministic by design where precision matters and LLM-based only where interpretation helps.
Forecasts
= Business Models + Market Signals
A universal, structured way to represent business models with explicit drivers and constraints. Forecasts aren’t statistical extrapolation; they’re grounded in how your business actually works.
Market Signals
= Narratives + Business Models
A methodology to generate quantitative market signals from LLM news digest narratives. External context that updates your models, not just your inbox.
Answers
= Templates + Analyses
A syntax to represent business questions in your own vocabulary. An extensive library of analysis and answer templates, deterministically linked to each question. Every answer traces to a defined analytical path.
Recommendations
= Forecasts + Impact Models
A curated knowledge base of business initiatives and deterministic analytics to estimate their impact on your specific context. Advisor doesn’t guess what to do. It calculates.
Conversations
= Templates + LLM
LLM integration to build narratives and explain results, within the boundaries of the models and templates. The conversational experience of an AI, with the precision of an engine.
Why this matters
LLMs hallucinate. Pure dashboard tools can't reason. Advisor's architecture solves both problems by using each technology only for what it does well, and putting deterministic logic in the path of every quantitative output.
Mechanic 02 · Business knowledge
Arrives understanding financial models, cost structures, and industry benchmarks.
Advisor doesn’t start from zero on each deployment. The platform comes with consulting-grade frameworks built in: financial models, driver trees, cost taxonomies, industry benchmarks, and analytical patterns drawn from twenty-five years of consulting work.
Your team doesn’t spend six months teaching the tool how your business works. The knowledge is already there. Each engagement enriches it further, creating a compounding capability that no LLM-only product can replicate.
Why this matters
This is the difference between a tool that helps your analysts and a tool that thinks like a senior consultant. Pre-loaded knowledge is what makes Ask answer like a partner rather than a search engine.
Mechanic 03 · Integration and data
Sits above your stack. Doesn't replace it.
Advisor connects to ERP systems (SAP, Oracle, Microsoft Dynamics, NetSuite), data warehouses (Snowflake, Databricks, BigQuery), and planning tools. The platform pulls what it needs, transforms and unifies the data, and runs analysis without disrupting your existing systems.
Data stays in your environment by default. Standard integration APIs handle the common cases; custom ETL handles the edge cases. The platform’s job is to make your existing systems useful for the decisions those systems weren’t built to answer.
What's supported
- Native connectors for major ERPs and data warehouses
- Standard ETL pipeline with re-run capability for ongoing data refresh
- Multi-entity, multi-currency, multi-language environments
- Self-service ETL configuration on the roadmap
Mechanic 04 · Delivery model
First results in weeks. Production in eight to fourteen.
A typical Advisor engagement takes eight to fourteen weeks to production. Clients see meaningful first results within the first few weeks, not at the end of a six-month implementation cycle.
Weeks 1–2: Align on taxonomies, identify data sources, build data requests. Weeks 3–4: Data pull, cleaning, normalization, categorization, validation. Weeks 5–6: Configure analytical modules, customize knowledge base, build business models. Weeks 7–8: MVP delivery, user demos, feedback collection. Weeks 9+: Refinements, additional use cases, training, handover.
After initial setup, the ETL pipeline runs on a regular cadence with minimal manual effort. The long-term direction is fully self-service ingestion and configuration.
Why this matters
Anaplan, Pigment, and Jedox implementations typically run six to sixteen months. Advisor delivers comparable depth in a fraction of the time because methodology is in the product, not in the consultants you hire to build it.
Positioning
What Advisor is not.
Buyers ask this question often, in different forms. Here are the four most common.
Not a BI tool.
Advisor makes recommendations, not dashboards. BI gives you the instrument; Advisor gives you the reading. You stop asking “what does the data say” and start asking “what should we do.”
Not an LLM wrapper.
Advisor is a hybrid system. Deterministic engines run the math. Language models narrate the results. The numbers are not the model’s invention. Auditable by design, with no hallucination risk on quantitative outputs.
Not a consulting firm.
Advisor embeds consulting-grade methodology permanently. The frameworks come pre-loaded; the analysis runs continuously; the capability stays after the project ends. You pay once for software, not twice for a recommendation.
Not an EPM replacement.
Advisor sits alongside your existing planning tools, not in place of them. It adds the strategic and advisory layer that EPM tools weren’t built to handle: new questions, novel scenarios, and recommendations grounded in your actual data.
Trust
Built for enterprise. Auditable by design.
The questions IT, security, and finance leadership ask before approving a deployment.
Auditability. Every number traces to source. Every assumption is editable. Every recommendation is logged with its reasoning. Outputs are reproducible and reviewable.
Data residency. Your data stays in your environment by default. Cloud deployment options are available; on-premise and private cloud are supported.
Security posture. Enterprise-grade authentication (SSO, SAML), role-based access control, audit logging, encryption at rest and in transit. Standard enterprise security review supported.
No hallucination risk. The hybrid architecture means language models never produce numbers directly. Every quantitative output is generated by deterministic engines and merely narrated by the LLM layer. The math is not the model’s invention.
Engineering DNA. Built by the founding engineering team that built Feedzai, the platform that handles billions of transactions per year at major banks. Enterprise reliability is the baseline, not an aspiration.
Schedule a working session.
Bring a decision you're trying to make, a use case you're trying to validate, or a stack you want to integrate against. Thirty to sixty minutes, structured around your specific situation, not a product tour.