Lead intelligence
The system scans historical company signals to find where tax recovery work might be worth a human professional's time.
SkatteRevision analyserar historiska svenska bolagsdata, iXBRL-årsredovisningar, domänregler och myndighetssignaler för att hitta återbetalningscase som revisionsbyråer annars måste gräva fram manuellt.
SkatteRevision is not a public SaaS product and not a replacement for authorized tax advice. It is a research and decision-support system that complements accountants, auditors, tax lawyers, and grant-backed innovation partners.
The system scans historical company signals to find where tax recovery work might be worth a human professional's time.
Outputs are designed as sourced workpapers: what was found, what legal basis applies, what is missing, and why the next step is justified.
The full system stays local because the data vault is large and valuable. Serious demos run directly from the development machine.
Company databases usually sell current status. SkatteRevision works backward across fiscal years to find missed positions, changed interpretations, hidden operational signals, and under-reviewed deductions.
Each track has different evidence requirements, risk gates, and professional handoff needs.
Finds companies where R&D-like work appears in historical reporting but may not have been converted into available payroll tax relief.
Identifies manufacturing and process industries where electricity use, permits, and case law may support recovery work.
Reviews vehicle and operating lease patterns for possible VAT recovery signals that require contract and usage verification.
Searches for investment and property-use patterns where the 10-year adjustment mechanism may matter.
Weak cases are stopped early. The system treats missing data as a sourcing task, not as permission to invent a number.
The best output is not a final tax filing. It is a partner-ready dossier that lets a qualified advisor decide whether to proceed.
Historical annual reports, iXBRL, registry snapshots, and local cache layers are normalized.
SQLite and vector stores make historical company signals queryable before any expensive research.
Hermes maps SNI and financial signals to the relevant specialist agents.
Risk-agent and Kritikern look for reasons the case should be killed or escalated.
Only high-quality cases become professional workpaper-style reports.
The current codebase is a local, polyglot research platform rather than a clean product repository. That is acceptable at this stage because the sellable asset is the data, the lead intelligence, and the repeatable workflow.
Python iXBRL parsers, corruption handling, Swedish taxonomy mapping, and bulk processing scripts.
Local SQLite databases and vector indexes for fast historical lookup before web research.
Express API, HermesOrchestrator, Azure AI Foundry routing, rate limiting, and agent prompts.
Core protocol, data-source hierarchy, insufficient-data handling, conflict checks, and PDF dossiers.
Dashboard panels for leads, telemetry, knowledge, scoring, reports, scripts, and local data inspection.
SkatteRevision can act as a second-look engine over existing and target-client portfolios. The firm keeps the client relationship and professional sign-off; TwistedStacks supplies the discovery and evidence-prep layer.
The system demonstrates applied AI in a concrete, revenue-linked domain: data engineering, legal reasoning, local-first infrastructure, agent orchestration, and professional workflow design.
A serious demo should not upload the data vault. It should run locally and show the workflow against a sanitized or partner-approved company case.
Use a sanitized sample, a public company, or a partner-provided org number.
Walk from local data lookup to agent routing, risk challenge, missing-data flags, and evidence notes.
End with what a qualified advisor would need next: client interview, accounting files, contracts, or FOIA.