Decision intelligence for capital allocation

The financial position that holds up under scrutiny.

Financial due diligence, ERP exports, management accounts and financial models rarely agree with one another. Organica reconciles conflicting evidence, computes the underlying financial position using deterministic logic and produces one transparent position an Investment Committee can defend.

Computed, not guessed

How it works, under the hood

From data room to one defensible number

Point it at a data room. Minutes later, the financials are reconciled, computed and validated - ready for the Investment Committee. Every step, every method, named.

Read 1

Data room

ERP · General Ledger · CRM · Contracts · Data-room PDFs

Language model · reads & classifies only
Compute 2

Financial reconciliation

Normalise · match · resolve variances between every version of the numbers

Deterministic · rule engine
Compute 3

Deterministic financial engine

Unit economics · EBITDA · cash flow · working capital - computed in code, never estimated

Deterministic · computed in code
Validate 4

Validation & source traceability

Detects inconsistencies · quantifies ranges · every figure linked to its supporting evidence

Statistical · Monte Carlo simulationStatistical · coherence checks
Decide 5

Investment Committee ready

One defensible number

IC memoranda · board packs · scenario analysis - every figure traceable to source

Deterministic computed in code, rule engine Statistical Monte Carlo, probabilistic checks Language model reads only, never computes a figure

The platform

AI reads. Deterministic logic computes.

Organica separates the two things AI is usually asked to do at once. Language understanding and financial computation are different disciplines, and the platform treats them that way.

Where AI works

Understanding the evidence

Artificial intelligence is used where it performs best: reading documents, classifying information, extracting relevant data and identifying patterns across ERP systems, financial models, CRMs, contracts and data rooms.

Where logic decides

Computing the position

Financial conclusions are computed through deterministic financial logic, never generated by probabilistic language prediction. Then every output is stress-tested before it reaches a committee:

Probabilistic ranges across assumptions, so an optimistic answer cannot quietly pass as fact
Internal coherence and statistical consistency checks
Complete traceability from conclusion back to source evidence

Case evidence

Built inside live mandates. Not on slides.

Organica is the productised version of a methodology that has been running inside real transactions for years - the team’s internal engine, now brought outside. Selected engagements, anonymised.

When 79% became 45%

Anonymized engagement · Technology transaction

In a competitive process, the management pack presented 79% of revenue as recurring. The figure was consistent across the CIM, the model and the data room, and the valuation multiple was built on it.

Reconciling billing data, contract terms and the ERP told a different story. Auto-renewing but cancellable contracts, re-billed services and one-off license true-ups had been classified as recurring. The contractually committed recurring share computed to 45%, traceable line by line to its source.

The Investment Committee debated the business, not the spreadsheet: the number was already defensible.
The valuation basis was corrected before the bid, not discovered in confirmatory diligence.
Every reclassified euro remained traceable to contract, invoice and ledger entry.
Reported · Management pack79%
Computed · Reconciled evidence45%

Same company. Same data room. One reconciled definition of recurring revenue, computed with deterministic logic and validated before capital moved.

The plan promised to double EBITDA. The evidence said: not through cost alone.

Anonymized engagement · European private equity
4,267data-room documents ingested and indexed, every figure traced to a source row
64 / 64ledger reconciliation lines independently reproduced - zero unexplained divergences
100,000 drawsof Monte Carlo simulation behind every forward-looking claim
Four evidence classesevery claim in the pack carries its class - OBSERVED, DOCUMENT, MANAGEMENT STATEMENT or MODELLED

The company was not too big - it was wrongly shaped.

Headcount sat comfortably inside the benchmark corridor, but one function was nine times its peer weight while the billable share trailed the industry norm. The restructuring story the deal had been priced on was the wrong story.

Cost alone could not reach the plan.

Across 100,000 simulated scenarios, not one reached the plan’s EBITDA endpoint through restructuring alone. That single finding reframed the deal from a restructuring case into a transformation-and-growth case - before capital was committed on the wrong thesis.

The plan’s first at-risk year was the next one, not the last one.

Testing management’s trajectory year by year against the levers actually available showed the plan front-loaded in margin and back-loaded in delivery - a governance finding that recalibrated the programme, its gates and its sequencing.

Pricing was the missing lever - and it could be priced.

A moderate increase inside the evidence-based no-switch band, supported by customer-loyalty metrics at the top of the industry range, was stated the way an IC needs it: as a base case under successful execution at roughly 70% probability - not as a headline promise.

We red-teamed our own numbers - and showed the client the grade.

The forward layer of any deal model runs on assumptions - the difference is whether anyone measures it. The independent review scored the model adversarially, and the grade went to the Investment Committee on its own page.

85/100Evidence layer · act on it
35/100Forward layer · do not bind capital on it
55/100Composite · decision-useful, not yet decision-grade

Together with the terms that turn assumptions into evidence: ring-fenced capital behind gates, deep commitments deferred until mechanisms are measured, confirmatory diligence before every escalation. A pack that hides its weakest layer invites the committee to find it. This one names it - and that is why the recommendation held.

Client identities withheld under confidentiality obligations. Figures rounded or expressed as ranges and ratios; probabilities are model outputs under stated assumptions, not forecasts. The methodology - ingestion pipeline, evidence taxonomy, three-part structure, adversarial self-review - is proprietary to Organica.

The growth rate said 141%. The truth was a fifth of it.

Anonymized engagement · SaaS pricing · DACH software

A PE-backed specialist software vendor in the SAP ecosystem - two decades in the licence business, several hundred enterprise customers - had to price its move to SaaS: without risking existing revenue, without pricing past the market, and without giving up the owner’s growth targets. Three versions of the truth sat in one management team: the CFO’s growth math, sales’ package instincts, and a business case nobody believed.

Organica harmonised 37 spreadsheets and more than 15 raw sources within hours - contracts, billing exports, volume time series, ticket data, real competitor offers. The forensics reframed everything: 6% of customers held 75% of the data mass, so the average described no real customer; and the 141% headline growth was mostly a migration artefact - flip-adjusted, organic growth was roughly a fifth of it. On that shared basis, three five-year pricing scenarios ran like-for-like on the same customers, benchmarked against six competitors from two evidence sources.

48 hours from the last raw data to a signed-off, decision-ready pricing strategy - the core analysis inside a four-week engagement, three scenarios, one clear recommendation.
Every core figure independently recomputed in two quality rounds. The CFO’s own review found zero corrections - and the sceptic became a sparring partner.
Revenue held in year one, mechanical growth thereafter through the built-in upgrade path, positioned at the competitive lower edge with a more specialised product.
Headline · reported growth141%
Computed · flip-adjusted organic≈1/5

Same data. One harmonised base. The migration artefact that would have broken every naive price model - named before the decision, not after it.

Client identity withheld under confidentiality obligations; relative figures only, absolute revenue, price and margin figures deliberately removed.

Capabilities

What Organica does for a decision

Evidence reconciliation

Brings operational, financial and commercial information into one consistent view of the business, and resolves the inconsistencies between sources.

Decision confidence

Measures how much evidence supports a recommendation before decisions are made, and quantifies the uncertainty that remains.

Continuous validation

Updates insights as new operational evidence becomes available instead of relying on one-time assessments.

Explainable intelligence

Every recommendation is transparent, traceable and supported by evidence rather than functioning as a black box.

Value opportunity detection

Identifies operational inefficiencies, improvement opportunities and value creation potential across the business.

Executive readiness

Generates Investment Committee memoranda, board packs, scenario analysis and decision-ready reporting from validated numbers.

Our promise

We don't tell organisations what to do. We help them understand their business well enough to decide with confidence.

Organica is currently working with a select group of investment professionals to pressure-test the platform. If your decisions move capital, we would value the conversation.