01 · Project
Case Evidence
Financial statements, contracts, models, board materials, operating data, and management assumptions—with every material fact tied to its exact source.
Your AI Companion in Financial Analytics
Turn Data Chaos
Into Decisions
You Can Defend
Nektus brings case evidence, valuation methodology, market knowledge, and your firm’s past work into one decision process. It helps your team identify what makes a case non-standard, challenge assumptions, and build conclusions that withstand scrutiny. Every material figure remains linked to its source. All sensitive data stays inside your network.
Beyond productivity AI
Faster Work Is Not the Same as Better Judgment
Most AI in finance helps work move faster. Nektus helps valuation teams decide what the evidence means. It keeps the method, assumptions, exceptions, and proof behind the final number in one governed process.
Establish the Evidence
Bring statements, models, contracts, board materials, and management assumptions into one source-linked case record.
Understand the Case
Explain the business, reconstruct the drivers, and identify what makes the asset or company different from a standard engagement.
Test the Method
Surface relevant methodology, benchmarks, required inputs, and limitations before a standard approach is applied to a non-standard case.
Challenge the Assumptions
Flag missing evidence, contradictions, unexplained adjustments, and conclusions that still depend on professional judgment.
Preserve the Decision
Keep the conclusion, its evidence, review history, and rationale together so the next challenge or update starts in context.
The wrong valuation method does not become right when applied faster.
A second opinion, built in
Every Valuation Case Has an Exception
Nektus does not force a standard template onto a non-standard business. It surfaces what makes the case different, which evidence is missing, and where the team must make an explicit professional judgment.
Spot the case-specific issue
Book value, accounting treatment, and economic value are not interchangeable. Nektus flags the assumptions that require a closer look before they enter the model.
Bring the relevant knowledge to the case
Methodology, market context, supporting evidence, and prior firm experience are considered together—not reconstructed across tabs and folders.
Keep the analyst in control
Nektus distinguishes supported findings from open questions and judgment calls. It strengthens the conclusion without pretending to own it.
The knowledge behind every decision
The Whole Case, Brought to One Table
Nektus does not answer from one document or one prompt. It connects the evidence in front of you with the methodology, market context, and institutional knowledge needed to interpret it.
02 · Method
Valuation Knowledge
Methodology, review rules, required inputs, limitations, and case-specific considerations developed with practitioners and maintained as a governed layer.
03 · Market
Market Context
Point-in-time benchmarks, comparable-company evidence, and industry context captured with the date, source, and assumptions needed for reproducible analysis.
04 · Firm
Your Firm’s Memory
Past engagements, accepted adjustments, reviewer comments, comparable searches, and the reasoning behind earlier decisions—retained as a reusable firm asset.
Nektus brings the council to the case: evidence analyst, valuation methodologist, critical reviewer, and institutional memory—without turning the final judgment into a black box.
The valuation team owns the conclusion. Nektus makes the path to it visible.Valuation-first by design
Valuation Intelligence for Corporate Finance and Private Markets
Built with valuation practitioners for decisions that must survive partner review, auditor questions, client scrutiny, and the edge cases where standard templates stop working.
From periodic exercise to continuous intelligence
A Decision Should Not Go Stale While You Prepare It
Traditional valuation separates evidence gathering from professional judgment. By the time the sources are assembled, reconciled, and reviewed, the context has already started to change. Nektus keeps the evidence and decision logic alive together.
The valuation paradox
You either freeze the inputs and defend a view that is already aging, or keep updating and never close the cycle. Nektus lets the team incorporate new evidence into the live case while preserving the method, assumptions, and review trail behind every change.
Update without restart
New board deck, KPI pack, or memo can refresh the active valuation context.
Methodology stays fixed
Assumptions, checks, and required evidence stay governed across cycles.
Review stays auditable
Every changed figure keeps a source link and a review trail.
Valuation over time
Illustrative
Valuation Inputs & Statement Extraction
IS · BS · CFS · Net Debt · Workbooks
Extract statements and notes from PDFs into structured workbooks, and collect DCF and multiples inputs — net debt bridge, share count, tax rate, capex, working capital — with every line linked to its source.
Continuous NAV & DD Updates
Monthly Cycles · Evergreen Funds · Annual Refresh
Refresh an existing valuation project when new data arrives. Update the active analysis instead of rebuilding spreadsheets and memos from scratch — an annual refresh becomes a recurring service instead of a new project.
Report & Model Review
Dates · Units · Contradictions · Broken References
Upload a finished memo or workbook and get a structured findings table — what the report says, what it should say, and why — before the document reaches the next reviewer, auditor, or client.
Consolidated Groups & Complex Assets
Entity Splits · Segment Metrics · Reconciliation
Pull entity- and segment-level metrics out of consolidated statements with reconciliation checks — and take on the opaque, non-standard assets that command the highest fees.
Market research
Poll data from valuation teams points to the same bottleneck — and it isn’t the model.
Source: Nektus poll in a professional valuation community, 83 respondents, 2026.
34%
cited frequent NAVs and transaction pricing as the strongest source of pressure.
59%
named data quality and availability as the biggest barrier to higher-frequency valuation.
50%
saw AI as useful for extraction, ingestion, structuring, standardizing, and labeling of valuation data.
35%
pointed to more complex or less transparent assets as the greatest pressure on valuation processes.
Why the work holds up
Trust Is Built Into the Decision Process
A valuation is useful only if the team can explain where the evidence came from, what the system computed, which method was applied, and where professional judgment entered the conclusion.
Numbers you can inspect
Calculated, Checked, and Source-Linked
Language models help classify, search, and write. Calculations and derived metrics run in deterministic code. Extracted values are verified, and every material figure keeps its provenance—document, page, table row, period, unit, and extraction method—so it can be checked in one click.
Evidence Before Assertion
Every key figure and conclusion stays connected to the paragraph, table, cell, or workbook it came from.
Methodology Before Improvisation
Required inputs, checks, limitations, and review rules are governed by the valuation workflow—not invented in an ad hoc prompt.
Judgment Made Visible
Supported findings, open questions, missing evidence, and reviewer decisions remain distinct throughout the engagement.
Private by Architecture
Documents, prompts, embeddings, outputs, and project memory stay inside your network. This is an architecture decision, not a policy promise.
Private & predictable
Enterprise-Grade AI Without the Enterprise Budget
Nektus makes private valuation intelligence practical for specialist firms: one annual software license, one server inside your perimeter, and no usage meter attached to every engagement.
One Annual License
A simple annual license covers the software, valuation knowledge and methodology updates, and support. No per-project fees, no usage meters, no surprise line items — costs stay predictable as your usage grows.
Light by Architecture
Specialized small models and deterministic workflows handle repeatable work. Model reasoning is used where context matters—not spent re-deriving the same structure on every run.
A Single Compact Server
Nektus runs on one GPU server inside your perimeter — hardware a mid-sized firm can actually buy and host. No data-center build-out, no cluster, no dedicated ops team.
The governed alternative
Decision Infrastructure, Not Another Chat Window
General-purpose AI can draft text and retrieve facts. Nektus maintains the evidence, methodology, calculations, review state, and project memory behind a valuation decision.
| Capability | Nektus Governed | Manual Work | Generic AI Agents | Enterprise Platforms |
|---|---|---|---|---|
| Your data stays self-hosted | Yes — zero outbound API calls | Yes | Often no — cloud model calls | Usually no |
| Numbers you can audit | Computed by code, with provenance | Depends on discipline | Model-generated, hard to verify | Varies by vendor |
| Domain methodology | Valuation knowledge and review rules built in | Depends on each analyst | Prompt-dependent | Requires implementation |
| Source traceability | Every figure linked to source evidence | Manual and inconsistent | Possible but fragile | Varies by vendor |
| Continuous updates | Update the active analysis with new data | Rework or manual refresh | Can summarize new files, not govern the cycle | Possible after integration |
| Upfront investment | Annual license + a single server | Headcount and turnover | Low cost, but data leaves the perimeter | Data-center appliance + integration project |
Prove it on work you already trust
Replay a Completed Valuation with Nektus
Use one finished engagement to test whether Nektus reconstructs the evidence, surfaces the same case-specific issues, supports the methodology, and exposes anything the original review missed.
1
Choose the Decision
Select one completed valuation with known evidence, methodology, reviewer comments, and a conclusion your team already trusts.
2
Rebuild the Case Record
Ingest the source materials, models, assumptions, and deliverables so Nektus can reconstruct the evidence behind the decision.
3
Replay the Analysis
Run extraction, checks, methodology support, and review workflows against the same material—without revealing the historical answer first.
4
Compare What Matters
Evaluate evidence coverage, methodology fit, issues caught, source traceability, review effort, and how defensible the reconstructed conclusion is.
Frequently Asked Questions
Valuation is the first and deepest decision domain in Nektus, and the focus of the product today. The underlying evidence, computation, workflow, and knowledge architecture is extensible to adjacent financial and due-diligence decisions through additional methodology layers.
Language models help classify, search, and write, while calculations and derived metrics run in deterministic code. Extracted values are verified, and every material figure keeps its provenance — document, page, table row, period, unit, and extraction method — so it can be checked in one click.
No. Nektus runs self-hosted within your network perimeter. Source documents, prompts, embeddings, model outputs, and generated artifacts stay inside your environment. This is an architecture decision, not just a privacy policy promise.
PDFs, Word documents, Excel workbooks, presentations, HTML and plain text, legacy office formats via OCR — and audio or video recordings, which are transcribed inside the perimeter. Any language, no manual reformatting before ingestion.
A single-GPU server inside your network — minimum one GPU with 80 GB of memory. No data-center infrastructure, no cluster, no specialized ops team.
Through a simple annual license that covers the software, valuation knowledge and methodology updates, and technical support. The hardware is owned by you. Total cost of ownership is a fraction of enterprise appliance cost.
It is the governed context Nektus brings to a case: valuation methodology, required inputs, limitations, review rules, point-in-time market evidence, and the firm’s own accumulated project memory. It helps the team interpret evidence without turning the final professional judgment into a black box.
General-purpose AI can answer questions and draft text, but it does not maintain a governed valuation process. Nektus keeps case evidence, valuation methodology, deterministic computation, source links, checks, open questions, and project memory together — and runs entirely inside your network.
It means a valuation project stays alive between reporting cycles. When new portfolio company data, board materials, lender reports, or management updates arrive, Nektus ingests them into the existing valuation context instead of forcing the team to rebuild the analysis from scratch. The same mechanism turns one-off engagements into repeat work: an annual due-diligence update starts from the living project, with Nektus flagging what went stale and pulling in the new data.
Yes. The recommended pilot replays one completed valuation using the same source materials. You compare evidence coverage, methodology fit, issues caught, source traceability, review effort, and the reconstructed conclusion against work your team already trusts.
Put Nektus Beside Your Team on a Real Valuation
Skip the canned demo. Replay one completed engagement with your evidence, methodology, and review standards. Then compare what Nektus understood, challenged, and preserved against the work your team already trusts.
- Fully self-hosted — your data never leaves your network
- Material figures checked and linked to their sources
- Annual license — a fraction of enterprise appliance cost