Generic AI lacks portfolio context
A model cannot answer a property-specific question reliably until the relevant records are organised and available.
AI property management · UK
AI that understands the history of your property portfolio.
Tenura is being designed to organise likely properties, documents, contractors and events before answering questions. The intended assistant shows whether an answer is stated, calculated or inferred and keeps its sources visible.
Pre-launch · Built first for self-managing UK landlords with roughly 5–30 properties
Ask Tenura
Reviewable answers with sources
Which properties need gas certificates this quarter?
2 properties need review
Gas Certificate.pdf
18 Wren Street
Gas Safety Record.pdf
4 Morland Mews
4
Properties
84
Documents
24
Contractors
Results are designed to remain linked to their sources
Why this exists
Property history should not depend on remembering where to look.
Summaries can hide uncertainty
An answer is more useful when you can inspect the invoice, certificate or agreement it was derived from.
Manual prompts repeat the work
Uploading one document at a time recreates the same search and sorting task for every question.
The working record
Ask the portfolio—not a generic model.
The fictional walkthrough answers questions about certificates, maintenance spend and tenancy dates from mocked records, shows the basis and highlights uncertainty alongside its sources.
Inbox reconstruction
The intended workflow prepares draft portfolio context before the first question.
Source-linked answers
Answers are designed to use identified portfolio sources rather than unsupported general knowledge.
Cross-property reasoning
Find patterns and records that span addresses, contractors and document types.
Inspectable evidence
Follow an answer back to the original attachment or email.
Clear product scope
Know exactly where Tenura fits.
Tenura is for
- Landlords who want AI retrieval grounded in their own records
- Portfolio teams repeatedly searching for dates, costs and documents
- Owners who value evidence as much as a fast answer
Tenura is not
- A legal, tax, investment or safety decision-maker
- An autonomous agent that contacts tenants or contractors
- A replacement for reviewing important original documents
Questions, answered
The practical details.
How is Tenura different from a general AI assistant?
Tenura first builds a structured property portfolio from connected email. Its answers are designed to use that portfolio context and reference the source, rather than relying only on general model knowledge.
What questions can I ask?
The illustrative demo includes questions about gas certificates, maintenance spend and tenancy dates. Production coverage and accuracy thresholds are still being developed.
Will AI answers always be correct?
No AI system should be treated as infallible. Tenura's source-first design makes answers easier to verify by opening the underlying evidence.
Does Tenura process my entire personal inbox?
Tenura is designed around read-only access and property-related information. Detailed production processing, retention and security terms will be documented before general availability.
Explore the product
Related Tenura workflows
Illustrative product walkthrough
See the review-first direction.
Walk through fictional portfolio data, sources and uncertainty. The demo does not access an inbox and is not a live customer account.