AWS
Where a great many enterprise workloads actually live. Connecting it means an assistant can answer about the state of the services your teams depend on, without anyone opening a console.
Where a great many enterprise workloads actually live. Connecting it means an assistant can answer about the state of the services your teams depend on, without anyone opening a console.
What AWS holds, and why that matters here
Most organisations that run anything at scale run part of it on AWS. What matters here is not the breadth of the platform but the small number of questions people ask about it repeatedly: is the service healthy, did the job finish, where is that file, what is this costing.
Those questions currently go to whoever holds console access. That is a small group by design, and it becomes a bottleneck the moment anyone outside it needs an answer — which is constantly.
The connection is read-only and scoped to an explicit list. Reading a job status does not need permission to start one, and reading a bucket listing does not need permission to write to it. That distinction is what makes this reviewable.
- Service health — what is running, what is degraded, what is scheduled.
- Job and pipeline state — finished, failed, still going, and when.
- Object storage — file presence and metadata, within named paths only.
- Cost and usage — where spend is going, for those entitled to see it.
- Tags and environments — which estate a resource belongs to.
Questions this connection lets Elbi answer
Is this service healthy?
Current state from your own monitoring, in a sentence rather than a dashboard.
Did that job finish?
Completion state and time, without opening a console.
Where is that file?
Presence and metadata within the paths you allow.
What is this costing us?
Spend by service or tag, for those entitled to see it.
Which environment is this in?
The tags as recorded, not as remembered.
Is there an incident open?
What is declared, so nobody files a second ticket for it.
How the connection works in practice
- You decide what is readableBefore anything is connected, you define the scope: which records, which fields, which operations. The assistant is given a narrow, named view of AWS rather than general access, and that view is agreed in writing during deployment.
- A question arrives in natural languageA customer or an employee asks something ordinary — "where is my order", "am I covered for this", "what did I spend last month". No syntax, no menu, no reference number required if the person is already identified.
- The assistant works out what is being askedThe question is matched to an intent and the details it needs. If something essential is missing, it asks for that one thing rather than presenting a form.
- It reads only what it is allowed to readThe lookup runs inside the permission scope you defined, and inside the permissions of the person asking. Someone who cannot see a record in AWS cannot see it through Elbi either — the assistant does not become a way around your own access rules.
- The answer is written back in plain languageA record is not an answer. The result is turned into a sentence in the language the question was asked in, with the parts that matter surfaced and the internal codes left out.
- Anything it cannot do goes to a personReads are safe to automate. Anything that changes money, entitlement or a legal position can be routed to a human for confirmation — you decide which side of that line each action sits.
Scope, control and what stays yours
| Direction of access | Read by default. Any write-back — creating a ticket, updating a record, logging a lead — is enabled deliberately, per action, and can be held behind human confirmation. |
|---|---|
| Who can see what | The assistant answers within the permissions of the person asking. Identity is established through your own sign-in, not invented by the assistant. |
| Credentials | The connection uses credentials you issue and can revoke, scoped to the narrow view agreed at deployment. Revoking access is something you do on your side, without our involvement. |
| Where data goes | Retrieved records are used to answer the question in front of the assistant and are not retained afterwards beyond your configured conversation retention. |
| Audit | Every lookup can be recorded — what was asked, what was retrieved, which agent, which conversation — so the connection is reviewable rather than opaque. |
| If it is unavailable | If AWS cannot be reached, the assistant says so plainly and offers a person. It does not guess at a value it could not retrieve, and it does not present a cached figure as though it were live. |
What this replaces
What this replaces is a queue in front of a small number of people. Console access is restricted for good reasons, so every question from outside that group becomes an interruption — and the answer is almost always a single field somebody reads off a screen.
The cost is invisible because it is distributed: two minutes here, five there, several times a day, spread across the people you least want interrupted. Nobody logs it, so nobody sees it.
The connection removes the middle step for questions that have a definite answer, and leaves anything requiring judgement — or any change at all — exactly where it was.
How different sectors use it
Engineering
Job and deployment state without breaking someone's focus.
Operations
Service health in plain language during an incident.
Finance
Spend by service and tag, on a schedule or on demand.
Data teams
Pipeline completion, without console access for everyone.
Support
Whether a customer-facing service is actually degraded.
Leadership
A straight answer about status without assembling a call.
Getting the value out of it
A connection is only as useful as the questions it is pointed at. The pattern that works is to start from the contact you already receive rather than from what the system can technically expose. Pull a month of chat transcripts and call notes, count the questions, and connect for the top five. That is almost always where the volume is, and it is usually duller than anyone expects — status, eligibility, balance, hours, documents.
The second thing that decides success is scope discipline. It is tempting to connect broadly and let the assistant work out what is relevant. It works far better to expose a small, well-named set of operations and expand once you have seen a month of real questions against them. A narrow connection is easier to reason about, easier to audit, and far easier to explain to whoever signs off on it.
The third is knowing what not to automate. Reads are safe. Anything that moves money, changes an entitlement or creates a commitment should either stay with a person or pass through one. The assistant is at its best when it removes the lookup and leaves the judgement.
What connecting it actually involves
- Agree the questions firstNot the fields, the questions. A month of real transcripts, counted, gives a ranked list of what people actually ask. That list decides the scope; the scope decides the connection. Starting from what AWS can technically expose produces a broad connection answering questions nobody asked.
- Define the readable viewYour team decides which records and fields the assistant may see, and which it must never see. This is written down, signed off, and is the document you will hand to whoever audits the deployment later.
- Issue scoped credentialsYou create the credentials, on your side, scoped to that view. They are yours: you can rotate or revoke them without involving us, and doing so takes effect immediately.
- Map your instanceCustom fields, renamed objects, local terminology and the particular way your organisation uses the system are mapped during deployment. Nobody has a stock configuration and the work assumes you do not either.
- Rehearse the unhappy pathsMissing record, ambiguous match, system unavailable, customer asking about someone else's account. These are tested deliberately before launch, because they are what determines whether people trust the assistant, and they are what most pilots skip.
- Launch narrow, widen on evidenceGo live on the top few questions, watch a month of real traffic, then widen. Every deployment that widened first and measured later has produced the same result: an assistant nobody trusts and a project that quietly stops.
Governing a connection you will have to defend
A connected assistant is a data-processing decision before it is a technology one. Under the Saudi Personal Data Protection Law, the questions that matter are the ordinary ones: what personal data is being processed, on what lawful basis, for how long it is kept, who can see it, and what happens when someone asks for it to be deleted. A lookup against AWS touches most of those at once.
The practical answer is scope and evidence. Scope means the assistant reads a narrow, named view rather than holding broad access, so the question "what could it see?" has a short and checkable answer. Evidence means every lookup can be recorded — the question, the retrieval, the agent, the conversation — so a review after the fact is reading a log rather than reconstructing a story.
The part most organisations underestimate is consent. If a customer is going to have their record read during a conversation, that has to be something they agreed to, in language they understood, in the language they speak. Retrofitting consent after launch is far more painful than designing the flow around it, and it is the single most common reason a pilot stalls at legal review rather than at the technical stage.
What organisations typically see
How this is done elsewhere, and where it goes wrong
The mainstream pattern across the industry is now well established: a conversational layer in front of systems of record, retrieving rather than remembering, escalating rather than improvising. Where deployments fail, they fail in recognisable ways.
The most common failure is connecting everything at once. A broad connection is harder to reason about, harder to permission correctly, and produces an assistant that occasionally surfaces something it should not — which is the single fastest way to lose internal trust and have the project shut down. Narrow beginnings survive; broad ones get switched off.
The second is treating the assistant as a reporting tool. Systems of record are optimised for transactions, not analysis, and an assistant asked to compute across large volumes will be slow and occasionally wrong. Point it at facts about a specific record and it is excellent; point it at "summarise our quarter" and it is the wrong instrument.
The third is forgetting the unhappy path. Systems go down, records are missing, a customer asks about an order that does not exist. What the assistant does in those moments defines how it is perceived far more than what it does when everything works — which is why saying "I could not reach that system" is a feature, not an admission.
Common questions
No. Read-only, scoped to an explicit list of services and paths. Reading a job status does not require permission to start one, and we do not ask for permission we do not need.
Only what you name. The scope is a list you write and can audit, not a role with broad reach.
Answers are bounded by the identity of the person asking. Somebody without entitlement to cost data does not get cost data through the assistant.
What is read is used to answer the question that prompted it. Nothing is copied into a second store, because a second store means drift and another thing to defend.
Each is scoped separately. Starting with one is faster and makes the review shorter.
By revoking the service credential. It is separate from anyone's personal access for exactly this reason.
No. The connection runs between your assistant and your system, using credentials you issue and control. What the assistant may read is the narrow scope you defined, and you can revoke it at any time without going through us.
Most deployments are. Custom fields, renamed objects and bespoke workflows are normal, and the connection is mapped to your instance during deployment rather than assuming a stock configuration.
It can, where you enable it. The default is read-only because that is the safe starting point. Write actions are turned on individually and can require a person to confirm before they commit.
Connect it to your own systems
A working assistant against your own records, in both languages.