The AI Workbench
for Defensible
Valuation Work
Nektus is a self-hosted AI assistant for valuation teams. It does the document and data work behind every engagement: pulling inputs from any source, keeping each figure linked to the evidence it came from, and turning each finished valuation into knowledge your team can reuse on the next one. Everything runs inside your network — built for analysts whose work has to hold up in front of partners, auditors, and LPs.
Local AI Agent
for Valuation
Turn Any Data
Into Insight
Data becomes knowledge only through work — careful, verifiable work. Time pressure cuts corners. Corners hide errors. Errors surface in front of clients. Your reputation is on the line every time. Nektus AI assistant helps you to extract structured, role-specific insight from any document type, keep every number linked to its source, and build a project memory your whole team can return to. Entirely inside your network.
Your Data Is Already There. Turn It Into Knowledge.
Data becomes knowledge only through work — careful, verifiable work. Time pressure cuts corners. Corners hide errors. Errors surface in front of clients. Your reputation is on the line every time. Nektus AI assistant helps you to extract structured, role-specific insight from any document type, keep every number linked to its source, and build a project memory your whole team can return to. Entirely inside your network.
Automate Valuation Workflows with Zero Data Compromise
Valuation analysts spend up to 70% of their time on mechanical work — extracting data, transferring figures, cross-referencing sources. Nektus automates this entire layer, running entirely within your network. No data ever leaves your perimeter.
Valuation Work Is Data Work
The model is the easy part. The real work — and where the judgment actually lives — is sourcing evidence, structuring inputs, pressure-testing assumptions, and keeping a record the team can stand behind later. A valuation is only as defensible as the work behind the number.
Documents Become Inputs
Portfolio company data arrives as PDFs, emails, board decks, workbooks, and management commentary. Nektus helps turn that unstructured material into valuation-ready inputs.
Every Number Needs a Source
Revenue bridges, EBITDA adjustments, debt figures, multiples, and assumptions are only useful if the team can trace them back to evidence. Source links are built into the workflow.
Valuation Knowledge Compounds
A finished valuation should not disappear into a project folder. Nektus turns prior work into searchable historical knowledge: assets, assumptions, adjustments, evidence, and reviewer rationale.
The Assistant Follows the Method
Nektus is an AI assistant inside a valuation process. It helps with extraction, questions, review, and exceptions while keeping methodology, approvals, and audit trails intact.
Poll data from valuation teams points to the same bottleneck — and it isn't the model.
Manual Valuation Is Always Late
If it takes X weeks to collect data and complete a valuation, the analysis is already X weeks stale when it lands. If new information arrives mid-process and you keep adding it, the finish line keeps moving.
You either freeze the inputs and ship a view that's already stale, or keep updating and never close the cycle. Nektus collapses the first pass to a fraction of the time, then lets the team fold new data into the live analysis instead of rebuilding it from scratch.
Built for Defensible Valuation Work
Speed matters only if the output can survive partner review, auditor questions, LP scrutiny, and regulator requests.
Valuation Project Memory
Every valuation cycle keeps source documents, extracted metrics, assumptions, scenarios, and review decisions in one persistent project. Next month starts from the current state, not from an empty folder.
Methodology-Driven, Not Improvised
The agent doesn't freelance. It follows your valuation methodology — required inputs, checks, assumption logic, scenario structure, documentation standards — so the same engagement runs the same way every time. A consistent process is what keeps drift and unconscious bias out, and what lets you defend the result cycle after cycle.
Source-Linked Outputs
Every key figure stays linked to the exact source paragraph, table, cell, or deck slide. When someone challenges a revenue bridge, multiple, or adjustment, the evidence is available immediately.
Document Review and Error Checks
Nektus can review an existing valuation memo or workbook, flag inconsistent assumptions, missing evidence, stale inputs, arithmetic issues, and unexplained movements before the document reaches the next reviewer.
Cost-Efficient Automation
Many B2B AI agents spend tokens by thinking through every small step. Nektus automates repeatable valuation work first and uses the assistant for review, exceptions, and judgment. Less token burn, lower energy use, better unit economics.
Private by Architecture
Valuation data, source documents, prompts, embeddings, and outputs stay inside your environment. No third-party model API is required, and sensitive data is not used to train external systems.
A Cost-Efficient AI Assistant for Valuation Teams
Nektus is not a generic agent loop that burns tokens to imitate a workflow. The repeatable valuation work is automated; the assistant is used where conversation helps: reviewing assumptions, explaining movements, finding evidence, and handling exceptions.
Where did this revenue input come from? Which document supports the EBITDA adjustment? Why did the multiple move? The assistant answers from the project evidence, not general knowledge.
Analysts, reviewers, partners, and audit teams work from the same project memory. No one has to reconstruct what changed, who reviewed it, or why a number moved.
Responses are grounded in specific documents, pages, slides, tables, or cells. You can verify the result in one click.
Valuation Workflows Nektus Automates
The product focus is narrow by design: make private markets valuation faster, more current, and easier to defend.
Data Extraction and Structuring
Extract valuation-relevant metrics from portfolio company materials, normalize formats, label inputs, and preserve links to the exact source evidence.
Continuous NAV Updates
Refresh an existing valuation project when new data arrives. Update the active analysis instead of rebuilding spreadsheets and memos from scratch.
Model Checks and Scenario Review
Check assumptions, source coverage, movement explanations, scenario logic, and unexplained changes before a valuation memo or model reaches reviewers.
Audit-Ready Documentation
Generate documentation that keeps methods, inputs, reviewer decisions, and source references together. Audit prep becomes the default state, not a year-end scramble.
Validate Continuous Valuation on a Historical Cycle
Run one completed valuation or NAV cycle through Nektus and measure what matters: time saved, how closely it matches the team's own conclusion, source coverage, and how the work holds up under review.
Scope the Valuation Workflow
Align on the asset class, valuation methodology, data sources, review requirements, and one historical cycle for the pilot.
Deploy Inside Your Perimeter
Configure the self-hosted appliance and ingest the source materials: workbooks, board decks, KPI packs, memos, and supporting documents.
Run the Valuation Cycle
Extract inputs, structure evidence, apply checks, generate review artifacts, and compare the Nektus output to the historical result.
Measure ROI and Governance
Evaluate time saved, token and hardware economics, how closely the output matches the historical conclusion, source-link coverage, review findings, and fit with your approval workflow.
How Nektus Compares to Alternatives
The question is no longer whether AI enters your valuation process — it's what kind. A generic chatbot can draft text but can't stand behind a number. Nektus is the governed alternative: an automation layer with a targeted assistant for exceptions, review, and evidence — built for firms whose work has to survive scrutiny.
| Capability | Nektus Governed | Manual Work | Generic AI Agents | Enterprise Platforms |
|---|---|---|---|---|
| Valuation data stays self-hosted | Yes — zero outbound API calls | Yes | Often no — cloud model calls | Usually no |
| Valuation methodology | Built into the workflow | 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 active analysis with new data | Rework or manual refresh | Can summarize new files, not govern the cycle | Possible after integration |
| Cost and energy efficiency | Automation first, assistant for judgment | Labor-intensive | High token burn from agent loops | High license and infrastructure cost |
| Audit-ready review | Checks, source links, and review trail | Prepared after the work | No governed approval trail | Depends on configuration |
Frequently Asked Questions
It means a valuation project stays alive between reporting cycles. When new portfolio company data, board materials, lender reports, or management updates arrive, Nektus can ingest them into the existing valuation context instead of forcing the team to rebuild the analysis from scratch.
Generic agents often spend tokens by planning, calling tools, checking themselves, and repeating small steps. Nektus automates repeatable valuation tasks directly and uses the assistant only where interactive judgment is valuable: exceptions, review questions, source explanation, and approval support. That reduces token burn, compute use, and cost per valuation cycle.
No. Nektus runs self-hosted within your network perimeter. Valuation source documents, prompts, embeddings, model outputs, and review artifacts stay inside your environment. This is an architecture decision, not just a privacy policy promise.
Nektus processes PDFs, DOCX files, presentations, spreadsheets, valuation workbooks, KPI packs, board decks, lender reports, and other portfolio company materials. No manual reformatting is required before ingestion.
Nektus is built around valuation methodology, source traceability, and governed workflows. General-purpose assistants can answer questions, but they do not maintain a defensible valuation process by default. Nektus keeps the workflow, evidence, checks, and review trail together.
Yes. Nektus can review an existing valuation memo or workbook and flag stale inputs, missing support, inconsistent assumptions, unexplained movements, source gaps, and arithmetic issues. The goal is to catch errors before partner, auditor, LP, or regulator review.
Nektus is designed for private markets valuation teams, NAV teams, audit and advisory groups, and investment teams that need faster valuation cycles without losing methodology control, source links, confidentiality, or review discipline.
Yes. The recommended pilot is a historical valuation or NAV cycle. We run Nektus on your source materials, compare the result to the completed analysis, and measure time saved, source coverage, review findings, and cost efficiency.
Larger firms are already moving, and clients increasingly expect faster cycles. But speed from a generic tool is a liability if no one can trace or defend the output. The durable edge isn't "using AI" — it's keeping your methodology and judgment in-house while automating the document and data work around them. Nektus is built so a boutique can move at that pace without handing its process, or its data, to a third party.
The valuation methodology layer can be updated without asking analysts to reinvent the workflow manually. Required checks, evidence expectations, approval steps, and documentation templates can evolve while the day-to-day process remains consistent.
See It Run on Your Own Valuation Cycle
Skip the canned demo. Request a pilot and run Nektus on one real, completed cycle — your source documents, your methodology, your review standards, inside your network. Then judge it against the work you already trust.
- Fully self-hosted - valuation data never leaves your network
- Methodology-driven workflows and source-linked outputs
- Cost-efficient automation with assistant support for review