عرض حيّ
Ultra RAG
محرّك البحث الذي يفهم وثائقكم ويذكر مصادره.
بحث معزّز بالاسترجاع مقترن برسم بياني للمعرفة، مضبوط حسب الثيمة: القانوني، وثائق المؤسسة، التسلسل الزمني. كلّ إجابة قابلة للتتبّع حتى الفقرة الأصلية.
جرّبه عبر الإنترنتعشرون دقيقة للعثور على بند. ثوانٍ، مع مصدره.
مستنداتكم — PDF وWord وExcel ومسوحات وعروض — تتحوّل إلى قاعدة معرفة تُستعلَم بلغة طبيعية. وكل إجابة تستشهد بالمستند والصفحة والفقرة التي جاءت منها.
- إجابة موثّقة وقابلة للتحقّق
- ضبط حسب الرصيد القطاعي
- إمكانية التوسّع إلى GraphRAG
The information already exists. It is simply not usable.
In most organisations the document estate is a dormant asset: assembled, paid for, never read again.
01
Scattered
Shared drive, mailboxes, three cloud spaces, archives, local disks. Nobody knows which version governs, and two copies of the same document circulate side by side.
02
Unstructured
Scanned PDFs, tables pasted into slide decks, annexes that amend a contract without saying so. None of it fits into a conventional database.
03
Partly obsolete
Some of the estate is no longer valid, and nothing flags it. Searching without separating current from expired produces confident, wrong answers.
What happens between your question and the answer
The engine does not guess: it searches, compares, checks, then writes from what it found.
01 / 05
Ingestion and normalisation
Documents are read whatever their format, scans included via OCR. Tables, annexes and attachments keep their structure. The date, version and origin of each item are retained — that is what will later separate current from expired.
02 / 05
Question analysis
The request is broken down: real intent, entities involved, constraints on date, perimeter or version. A question about “the contract in force” is not the same as “every contract signed with this supplier”.
03 / 05
Hybrid retrieval
Semantic search and exact keyword search are combined, then passages are re-ranked by actual relevance. References and article numbers, which semantic search alone systematically misses, are found.
04 / 05
Connecting the dots
When the relationships between pieces of information matter — linked contracts, successive versions, subsidiaries, amendments — the knowledge graph connects the entities. That is the difference between finding a document and understanding what amends it.
05 / 05
Sourced drafting
The answer is built from the retained passages, and each element links back to the document, page and paragraph. If sources contradict each other, the contradiction is flagged rather than silently resolved.
Two levels of use
Direct querying is the starting point. The agentic layer is what turns search into work done.
Direct querying
You ask, the engine finds the information and answers with its source. “What commitments does this contract contain?” gets an answer in seconds.
Document comparison
Two versions, two contracts, two bids: the agent identifies the real differences, not just wording changes, and lays them out line by line.
Structured extraction
Pulling a usable table out of a document estate: expiry dates, amounts, termination clauses, owners, in the format you impose.
Summary and report
The agent reads several documents, structures the information to your template and produces the note or report, with sources appended.
Deliverable generation
A Word document on your template, a slide deck, a table: the deliverable comes out in the expected format, ready to review, not to reformat.
Multilingual corpora
The engine indexes and queries document estates in several languages at once, and answers in the language of the question.
Tuned per corpus, because a contract does not read like a support ticket
“Tuned” means the algorithm itself changes with the corpus: passage weighting, chunking, version handling, date treatment. It is not a cosmetic setting.
- Legal / regulatory profile
- Priority to exact wording, article numbers and the version in force at a given date.
- Catalogue profile
- References, variants and technical characteristics, where one digit changes the product.
- Corporate document profile
- Procedures, minutes and internal notes, where the most recent version governs.
- Temporal profile
- Corpora where chronology carries the meaning: decision histories, chains of amendments, incident series.
- GraphRAG
- Graph modelling when relationships between entities matter as much as document content.
- Deployment
- SaaS hosted in the European Union, on your cloud, or entirely on your own infrastructure.
Three document estates, three tunings
01 · السياق
Twelve thousand engagement documents scattered between the server and team folders. Finding a precedent takes twenty-five minutes, when you know it exists.
02 · ما ننفّذه
Document layer with the corporate profile, isolation by team, and structured extraction to assemble reference files.
03 · النتيجة
The precedent is found in under two minutes, with the original deliverable and the engagement name. The estate becomes an asset again.
01 · السياق
The contract portfolio lives in a shared space. Nobody can say, without reading manually, which contracts carry an automatic renewal clause.
02 · ما ننفّذه
Legal profile with a knowledge graph: contracts, amendments and parties linked, with version and effective-date handling.
03 · النتيجة
The question is asked in one sentence and the answer arrives with the list, the articles and the deadlines. Amendments stop being forgotten.
01 · السياق
Technical sheets, standards and calculation notes have accumulated over fifteen years, in mixed formats including many scans.
02 · ما ننفّذه
OCR over the legacy estate, catalogue profile for technical references, and structured extraction into a usable table.
03 · النتيجة
Technical data becomes queryable again, including what was locked inside scanned paper documents.
What we measure at pilot
The error rate is measured on your documents, with your real questions, before any industrialisation.
- search time on the questions covered by the indexed corpus
- -90 %
search time on the questions covered by the indexed corpus
- of answers citing document, page and paragraph
- 100 %
of answers citing document, page and paragraph
- between pilot launch and the decision to industrialise
- 6-10 weeks
between pilot launch and the decision to industrialise
هذه المقادير مستمدّة مما نقيسه في المرحلة التجريبية على نطاقات مماثلة. أما على رصيدكم فتُقاس قبل التصنيع، ولا يُوعَد بها مسبقًا.
ما يمكنكم رؤيته يعمل الآن
هذه المنتجات مبنية بالفعل. بعضها متاح عبر الإنترنت، والباقي يُعرض عند الطلب.
عرض حيّ
Legal-Index
البحث القانوني موكولًا إلى وكلاء مستقلّين.
البحث في النصوص والاجتهاد القضائي، وتحليل العقود، والمساعدة في الصياغة. كلّ إجابة تحيل إلى المادّة وإلى النسخة السارية في التاريخ الذي يهمّكم.
جرّبه عبر الإنترنتأسئلة شائعة
Native and scanned PDFs, Word, Excel, PowerPoint, plain text, images containing text, exports from business tools. Scans go through an OCR layer before indexing.
It links entities together — a contract and its amendments, a company and its subsidiaries, a standard and its versions. Without it you find documents; with it you understand what changes their scope.
Date, version and origin are captured at ingestion, and the search profiles use them. On a legal corpus, the version in force at a given date wins. That assumes the estate can be dated — otherwise, that is the first project.
Never. The corpus stays isolated by organisation, team and user, and the agent's rights are those of the person asking.
Yes, on your infrastructure or private cloud, including with self-hosted models when corpus sensitivity requires it. That is the standard case on regulated estates.
From a few hundred to several hundred thousand documents. Beyond a certain volume the question is no longer size but the quality of the estate and the granularity of access rights.
ما لا يفعله هذا الحل
We do not deploy a document layer on a false or obsolete estate. An excellent engine on an expired corpus produces wrong answers that are sourced and convincing — worse than no engine at all. We say so at scoping and start with the cleanup, which is a project in itself. Nor do we claim one hundred per cent reliability: we promise traceable answers and a measured error rate.
How many documents are asleep on your server?
Bring a representative sample to the diagnostic. We will tell you what is usable as is, and what needs cleaning first.