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Private AI assistant for organizational knowledge

Turn organizational knowledge
into a conversation.

Build answers from your organization’s documents, decisions and experience. Simurgh turns authorized sources into searchable knowledge, summaries and reports, on infrastructure you control.

Start exploring your needsCompare editions
Private deploymentSource-based answersAccess control
Simurgh knowledgeInteractive view · Sample data
Knowledge scopeProject knowledgePrivate
Your question

What was the latest rollout decision, and what is still open?

SIMURGHAnswers supported by sources

The rollout will be phased, starting with one unit.

Final approval of user access remains open.

Answer support2 sample sources
Decisions section
Initial rollout in one unit was approved; expansion to other units will follow evaluation of this stage.

Select a source number to read the relevant passage.

FROM KNOWLEDGE TO INSIGHTQuestion · Answer · Review

A closer look

Product brochure & demo

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Product demo Simurgh

The story of the Simurgh

Connecting knowledge. Illuminating the way.

When the thirty birds looked, they saw at once:Those thirty birds were, beyond doubt, the Simurgh.

Attar, The Conference of the Birds; thirty birds before the Simurgh ↗

In the Shahnameh, the Simurgh raises Zal and comes to his aid in times of difficulty. The feather it entrusts to him is a keepsake of an enduring bond—a sign that his guide will return to his side when needed. In this story, the Simurgh embodies wisdom as a companion: understanding that lights the way.

In another tale, Attar’s The Conference of the Birds, thirty birds undertake a difficult journey in search of the Simurgh and reach a new understanding of themselves. For us, this image offers inspiration for bringing knowledge together: every experience is part of a larger picture, and meaning emerges when we see those experiences together.

Simurgh by Faraconesh draws inspiration from these two images: guidance when it is needed and connections between scattered knowledge. It brings together an organization’s documents, decisions and experiences within each user’s access permissions, so people can ask questions of their organization’s knowledge, examine the evidence behind the answers and make better-informed decisions about what comes next. Knowledge that stays in your private infrastructure and becomes useful again in the flow of work.

Yesterday’s experience, in today’s answers. Knowledge for the next step.Ferdowsi, Shahnameh; Zal’s upbringing ↗

Simurgh at a glance

The knowledge is there.
Find it when you need it.

Simurgh is a private AI layer over your organizational knowledge.

It brings documents, reports, minutes and authorized sources together in a controlled space. Users ask in natural language, retrieve relevant content and receive answers and summaries for analysis and decisions.

Fragmentation

The answer to one question is hidden across several documents.

Bring relevant context from different sources together.

Organizational memory

When people move on, their experience becomes hard to reach.

Put recorded history and decisions back to work.

Confidentiality

Sensitive knowledge requires an environment you control.

Manage data, models and access in a private architecture.

For knowledge-driven organizations

Knowledge management, data and AI, IT, PMO, operations and security teams: wherever documents are plentiful, experience valuable and timely answers needed.

Answer journey

From your question to the answer’s evidence.

Simurgh brings organizational knowledge into conversations by retrieving relevant content and using it to generate answers. This is the basis of RAG architecture.

Conceptual RAG viewStage 2 of 4

Semantic retrieval

Simurgh retrieves passages related to the meaning of the question from authorized sources, even when its exact wording does not appear in the document.

Input to this stage
Query authorized sources
Result of this stage
Relevant passages from multiple sources

Simurgh in everyday work

From reading piles of documents to using knowledge.

Questions, summaries, comparisons, extraction and drafts, aligned to your sources and goals.

An everyday request

«What is the summary of these minutes?»

Sample output

Decision: phased rollout. Next action: complete the user list. Open item: access approval.

Sample source: Sample minutes · Decisions and actions
FIND

Semantic search

Find relevant documents, decisions or experience based on the question’s meaning.

VERIFY

Answers with citations

Display sources or relevant passages where citation support is available.

CONFIGURE

Specialist assistants

Configure behavior, terminology, response format and sources for each unit or use.

IMPROVE

History and feedback

Revisit authorized conversations and collect feedback to improve quality.

Knowledge and access governance

Each team’s knowledge,
within its own boundaries.

Knowledge spaces and source collections define each assistant’s answer scope. User roles and permissions are respected during retrieval.

Defined sources
Knowledge collections for different units, projects and applications.
Configurable behavior
Instructions, specialist language and output formats tailored to each team’s work.
Trackable improvement
Authorized history and feedback to evaluate and improve answers.
One organization, multiple knowledge spacesConceptual view
Sample access scope

Project knowledge space

1Meeting minutesAuthorized source
2Progress reportsAuthorized source
3Decision recordsAuthorized source
Project assistant

Summarize decisions, open items and next actions with references.

«Why did the project decision change?»

Retrieval stays within authorized sources, based on users, groups and roles.

Simurgh editions

One private core. Two knowledge domains.

Enterprise covers general organizational knowledge and Security specialist security knowledge; your questions and sources guide the choice.

Shared core: Private AI, knowledge retrieval, access control and configurable assistants.

Compare each edition’s needs, sources and outputs.
Selection criterionSimurgh EnterpriseSimurgh Security
Main challengeAccess scattered knowledge and reuse organizational experienceMake specialist knowledge and experience accessible to security teams
Knowledge sourcesPolicies, minutes, reports, documentation and project recordsIncident reports, playbooks, controls, assessments and lessons learned
Typical outputSourced answers, summaries, extracted decisions and report draftsRetrieve similar experience, specialist answers and security report drafts
UsersKnowledge management, PMO, operations, IT and decision makersSOC, CERT/CSIRT, security engineering, risk and compliance
Starting prerequisitesSelected documents, authorized users and real questionsSelected security knowledge, analysis scenarios and assistant responsibility limits

Simurgh Enterprise

Main challenge
Access scattered knowledge and reuse organizational experience
Knowledge sources
Policies, minutes, reports, documentation and project records
Typical output
Sourced answers, summaries, extracted decisions and report drafts
Users
Knowledge management, PMO, operations, IT and decision makers
Starting prerequisites
Selected documents, authorized users and real questions

Private deployment and integration

AI where your data lives.

Deploy on internal infrastructure or a private cloud, choosing models suited to language, required quality and organizational hardware resources.

Organizational infrastructure boundaryPRIVATE AI
Authorized sourcesDocuments and systems
Knowledge spacePreparation and retrieval
Private modelAnswer generation
Authorized userAnswer and review

Data, knowledge and models can stay within this boundary.

A model suited to the problem

Model choice considers real questions, language, quality and response time.

Can be designed for offline use

Models, data and integration dependencies are reviewed for offline operation within the deployment scope.

Connected to existing sources

APIs, webhooks and configurable flows ingest knowledge from organizational systems, with connectors approved per project.

Start with a clear scope

One knowledge collection. Real questions. A quality criterion.

We define sample documents, authorized users, confidentiality levels and expected output, then evaluate retrieval and answer quality in that scope.

Start independently; expand alongside Faraconesh products.

Integrations are designed according to requirements and project scope.

HodhodIncident experience as a knowledge sourceShahbazRelevant knowledge for investigationHomaAssessment and improvement knowledgeShabdizProtect input data

Before choosing

Frequently asked questions

Automatic playback · Paused

With internal or private deployment, models and data can stay and run within organizational infrastructure. For offline environments, model dependencies, data ingestion and integrations are reviewed during deployment design.

Next step

Your organization’s knowledge:
which questions is it ready to answer?

Let’s review sources, users and key questions to identify Enterprise or Security and define the initial scope.

Start exploring your needsTalk to the Faraconesh team