The organisation, understood
01 Connect
Connect to organisational systems, data, workflows and integrations.
systems · data · workflows
Enterprise AI · for government and enterprise
Your institution's own AI, inside your own perimeter.
- Sovereign deployment
- Nothing leaves your perimeter
- Every answer audited
- Arabic and English
01/The distinction
It should not onlyanswer questions.
An AI operating layer understands the organisation, identifies where value is being lost, recommends the right intervention and puts it into action.
Understanding
It understands the organisation first.
Enterprise search, advanced RAG, knowledge graphs and complex document retrieval give the platform a deep understanding of organisational knowledge, systems and operations.
Knowledge Hub · the intelligence layer
Action
Then it turns understanding into action.
AI employees, workflows and the enterprise workspace turn that understanding into measurable operational outcomes across service, operations and decision making.
Shaffra Work + Build · the operational engine
Connects to what you already run
- SharePoint
- SAP
- Oracle EBS
- ServiceNow
- Salesforce
- Microsoft 365
- Confluence
- Jira
- PostgreSQL
- File shares
- Contact centre
- HRIS
- Ticketing
- + your own APIs
Read only by default and deployed within your network, inheriting the permissions already enforced across your systems. Access remains governed by the same organisational controls.
02/The operating loop
Eight steps. One continuous operating loop.
A continuous operating loop that understands the organisation, identifies where intervention is needed, deploys the right AI capability, governs the outcome and continues into the next priority.
The circuit
A continuous operating loop that understands the organisation, identifies where intervention is needed, deploys the right AI capability, governs the outcome and continues into the next priority.
eight steps · one loop
The organisation, understood
Connect to organisational systems, data, workflows and integrations.
systems · data · workflows
The organisation, understood
Organise and understand organisational knowledge through search, advanced RAG and knowledge graphs.
RAG · search · knowledge graphs
The organisation, understood
Give employees one workspace to access organisational knowledge, systems and AI employees.
one workspace · Arabic · English
The organisation, improved
Identify inefficiencies, operational problems and AI intervention opportunities.
bottlenecks · cost · cycle time
The organisation, improved
Recommend the right AI interventions, including which AI employees to deploy and where.
AI employee · role · deployment
The organisation, improved
Deploy autonomous AI employees and teams into production workflows.
into production workflows
The organisation, improved
Govern every deployment through security, permissions, monitoring and performance management.
permissions · monitoring · audit
The organisation, improved
Continuously identify the next area for improvement and expand the deployment.
the next area, and the next
The loop, closed
If hiring cycles begin to slow, the platform can recommend and deploy an AI Recruiter. If sales opportunities are stalling, it can deploy AI sales employees to strengthen inbound response.
The loop continues, expanding into the next organisational priority
01Connect
02Understand
03Interact
04Identify
05Recommend
06Deploy
07Govern
08Expand
08 / 08Closed
The organisation, understood
01 · systems · data · workflows
Connect
Connect to organisational systems, data, workflows and integrations.
02 · RAG · search · knowledge graphs
Understand
Organise and understand organisational knowledge through search, advanced RAG and knowledge graphs.
03 · one workspace · Arabic · English
Interact
Give employees one workspace to access organisational knowledge, systems and AI employees.
The organisation, improved
04 · bottlenecks · cost · cycle time
Identify
Identify inefficiencies, operational problems and AI intervention opportunities.
05 · AI employee · role · deployment
Recommend
Recommend the right AI interventions, including which AI employees to deploy and where.
06 · into production workflows
Deploy
Deploy autonomous AI employees and teams into production workflows.
07 · permissions · monitoring · audit
Govern
Govern every deployment through security, permissions, monitoring and performance management.
08 · the next area, and the next
Expand
Continuously identify the next area for improvement and expand the deployment.
If hiring cycles begin to slow, the platform can recommend and deploy an AI Recruiter. If sales opportunities are stalling, it can deploy AI sales employees to strengthen inbound response.
03/The control layer
Answering is the easy part.
The harder part is everything around it. Six layers govern how a response is produced, retained and explained, so an institution accountable for every word it publishes can show exactly how each one was reached.
01/Agent runtime
Every step is visible before anyone has to ask.
The platform classifies, gathers and resolves. Each step is declared before it executes and recorded once it has, so an auditor can replay how an answer was reached rather than take it on trust.
- Runs
- on every request, ahead of the model
- Leaves behind
- a trace an auditor can replay line by line
02/Guardrails
Your policy, compiled.
Your organisational policies run before and after every response. When a rule is triggered the answer is held, recorded and routed according to that same policy, and nobody has to notice it happening.
- Runs
- on every request and again on every response
- Leaves behind
- the rule that fired, with the answer it held
03/Privacy layer
Company information stays outside the model.
Names, identifiers and account details are replaced with placeholders before a request leaves your perimeter, and restored when the response returns. The model never receives them and the transcript never holds them.
- Runs
- inside your perimeter, before anything leaves it
- Leaves behind
- a transcript with no identifier in it
04/Classifier
Decades of files, organised overnight.
Entities are extracted from PDFs, call recordings and spreadsheets, matched across sources and organised into your own taxonomy. A fragmented archive becomes a connected graph without anything being retyped.
- Runs
- across documents, recordings and spreadsheets
- Leaves behind
- a graph with a path back to every source file
05/Insight board
The layer that answers also reports.
Retrieval that can name its sources can also count them. You see what the organisation asks, what resolves without a human, and where attention is needed next, from the same layer that produced the answers.
- Runs
- on the same retrieval that serves the answers
- Leaves behind
- counts by queue, by intent and by language
06/Agentic layer
Decides, deploys
It decides who the work needs next.
It reads what the rest of the platform reports, recommends the AI employee that closes the gap, sets the first action that employee will take, and deploys it once you approve.
- Runs
- on what the other five layers report
- Leaves behind
- a recommendation, and the employee that closes it
- 01
- 02
- 03
- 04
- 05
- 06
You charged me twice for November.
- Classifybilling dispute, confidence 0.9440 ms
- Gatherbilling ledger, 3 rows88 ms
- Resolverecomputed the pro rata210 ms
November was billed twice, on the 3rd and the 6th. The duplicate is refunded under reference 88-2041. Every step above is recorded and can be replayed line by line.
Can you give me 30% off if I sign today?
- Identityverified against the account30 ms
- Scope FIN-02outside the approved rate sheet18 ms
- Holdresponse stopped before it was sent6 ms
I am not able to approve that discount. The request has gone to your account manager with the rule it breached attached, so nothing was quietly softened on the way out.
Where has Ahmed Al Balushi's transfer request got to?
- SubstitutePERSON_1 and ID_1 swapped in before the request left9 ms
- Retrievematched against the placeholders120 ms
- Restoreidentity returned on the way back7 ms
It moved to final review on 12 March and is with his line manager. The model never received his name or his employee number, and the transcript holds neither.
What is actually in the 2019 archive?
- Ingest412 PDFs, 96 call recordings, 38 spreadsheets4.2 s
- Extractentities matched across all three sources1.8 s
- Fileorganised against your own taxonomy260 ms
1,240 contracts covering 380 suppliers, each linked to the calls and the correspondence that mention it. Every entry keeps a path back to the file it came from.
What has the organisation been asking this week?
- Count12,400 questions answered, up 112%60 ms
- Resolve rate84% closed without a human35 ms
- Rankslowest queue isolated80 ms
Gulf dialect calls are the fastest growing queue and are on course to cross your service level in about forty minutes. Everything else is inside target.
Hiring is taking far too long. What should we do about it?
- Readhiring cycle at 41 days, 13 longer than last quarter180 ms
- Score rolesAI Recruiter 94, AI Interviewer 61240 ms
- Checkcapacity and permissions confirmed55 ms
Deploy an AI Recruiter. It closes this gap and can start on the backlog today.
Recommended
AI Recruiter
First action, screen the 340 applications already open, then book the shortlist.
- Runs inside your perimeter in a sovereign cloud, on premises or in an air gapped environment
- ISO 27001
- Row level permissions inherited from your own systems
- Full audit trail on every answer
- Native Arabic and English
- Designed to support 10 TB and 10,000 users
04/One front door
Your people meet all of it in one workspace.
Employees reach organisational knowledge, connected systems, AI employees and workflows from a single workspace in Arabic and English, governed by the permissions your organisation already enforces.
It is also the command centre. Leadership can ask about the business and see what is running right now, including today's numbers, current priorities, emerging risks, decisions awaiting human input and the work of every AI employee as it happens.
05/The ask
See it run onyour own knowledge.
Bring one department and one week of real questions. We will show you what the platform understands and where it can act.