Stop your AI from guessing. Feed your agents verified, real-time UK corporate intelligence via a single, low-latency API. Eliminate hallucination. Stop the slop.
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Research assistant
Grounded company research
Build an investigation
Choose a company and the decision your agent needs to make.
Account monitor
Scan new accounts filings, then rank only the companies whose published results warrant a commercial-finance conversation.
Monitor summary
201 companies scanned. Three newly filed accounts merit a commercial-finance review; the remaining filings did not clear the monitor’s threshold.
00368850 · Accounts filed 26 Aug
Turnover fell 17% and the annual loss widened to £5.3m; the filing reports net liabilities of £366k. Directors cite group cash pooling and ultimate-parent support in their going-concern assessment.
Commercial signal: working-capital pressure sits alongside an acquisition-transition and parent-support story.
16107598 · Accounts filed 25 Aug
Latest accounts show a £2.5m operating loss, negative funds of £1.9m and £102k cash against £6.4m of current creditors. Two outstanding charges are recorded.
Commercial signal: the filing supports a restructuring or asset-backed-finance use case, rather than unsecured growth funding.
03496115 · Accounts filed 21 Aug
The legal entity reports a £6.8m operating loss, negative funds and six charges. Its filing says directors rely on group banking headroom and stress testing, with a specific risk that projected growth is not achieved.
Commercial signal: any funding rationale belongs at group level, with the disclosed banking headroom and growth assumptions central to the case.
Energy watch
Compare annual disclosures from operating businesses using 100–500 GWh, excluding electricity, gas and steam suppliers.
What the agent found
Sofidel UK’s total reported energy use is broadly stable, but its fuel mix changed materially in 2025. That makes this an energy-transition and efficiency conversation, not a generic high-consumption alert.
02245657 · paper manufacturing · four UK sites
’23
459.7 GWh
’24
459.4 GWh
−0.1%
’25
461.7 GWh
+0.5%
In ’25, natural-gas use fell 0.8% while electricity increased 2.0% and other fuels rose 69.5% from a low base. The company reports work on a dual-fuel boiler, biomass, photovoltaics and hydrogen fuel switching.
Grounded implication: the disclosed fuel-switching and on-site-generation work creates a specific efficiency, energy-services and asset-finance rationale at the relevant site.
General-purpose models operate on probability, often hallucinating revenue figures, inventing directors, or misinterpreting solvency. When building autonomous agents for CRM, Trading, or Risk, 'close enough' isn't good enough.
You don't need another generative layer; you need a deterministic truth layer.
Three pillars of truth for your agentic architecture.
The Foundation.
Instant access to hard facts. Fetch standardized financial reports, director mappings, import-export activity, ESG metrics and much more. Cleaned, codified, and ready for ingestion.
The Discovery.
Market-wide queries. Allow your agents to query the entire dataset. "Find logistics companies in Yorkshire with >£5m turnover and declining liquidity."
The Context.
Clean evidence for agent reasoning. Pull pre-tagged financial filings, news, and website context so your AI sees the exact passages that matter, not a noisy pile of scraped text.
{
"company_name": "Acme Logistics Ltd",
"turnover": 5200000,
"risk_score": 12,
"solvency_trend": "DECLINING",
"magic_insight": "High churn risk detected due to recent director resignations and deferred tax liabilities.",
"grounding_confidence": 0.99
}Designed for the modern AI stack. Whether you are building in Python, Node, or Go, our schema is strictly typed and documented in OpenAPI 3.0.
The engine room of the UK economy, indexed.
Full P&L, Balance Sheets, Cash Flow history.
Directors, Shareholders, Persons of Control.
Import/Export, Credit Risk, Legal Notices.
Emissions data, Energy usage, Governance.