The answer needs a room of specialists and a meeting.

Answers about the company, with the sources shown.

AI Insight reads the same things a room of specialists would: the strategy documents, the processes, the workflows and their runs, the systems and the data flowing between them. Ask a question and it answers in a few seconds with its sources shown. Ask what a change would touch and it lists every affected area before anything is built.

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The assistant answers a company question, scopes a change and builds it Asked why new-region sign-ups dropped, the assistant answers from the strategy, the onboarding process, the payment workflow's retries and the billing data in a few seconds. Asked to add a back-off retry, it lists the five places the change affects, including a portal label that was not mentioned. Once accepted, planner, reviewer and worker build it, test it in staging and promote it to production. STRAX assistant Why did new-region sign-ups drop last week? StrategyNew-region growth is a Q1 objective ProcessOnboarding, step 4 · payment WorkflowPayment step retried 41 times on Tuesday Data41 sign-ups abandoned at payment · billing events Sign-ups fell after the payment-gateway timeouts on Tuesday. Answered in 6 s Answered with sources, in six seconds. Add a 2-minute back-off retry to the payment step. Affects 5 places: Onboarding workflow Support-desk ticket rule Billing mapping Revenue report · pending Portal label · not in the request Accept Planner ✓ · Reviewer ✓ · Worker ✓ Drafted Staging ✓ Reviewed Production Built and live in 4 min 5 changes · approved by T. Mokoena What it knows · live Strategyread ✓ Processesread ✓ Workflowsread ✓affected Systemsaffected Dataread ✓ Portalsaffected Reportsaffected Your model · hosted or fully local Ask anything about the company, and see what a change would touch.

Answers about what is happening

Why did sign-ups drop last week? Which process does this ticket belong to? What happens to billing when a customer changes address? Questions like these usually need a room of specialists and a meeting. AI Insight answers them in a few seconds because it reads the same things the specialists would: the strategy documents, the processes, the workflows and their runs, and the systems and the data flowing between them. Every answer cites its sources, so you can see how it got there.

  • Reads strategy, processes, workflows, mappings, runs and logs as they are now.
  • Answers in plain language with its sources shown, from the boardroom question down to the record that caused it.
  • Diagnoses a failed job, a slow source or a missing step the same way, one click from the screen it happened on.
Live Ask the business anything Data, processes and documents, one answer
Ask the business anything A plain-language question is asked; the copilot's sources (current data, process maps, documents) light up in turn; the answer arrives with its sources cited. Asked in the boardroom, typed as said: "Why did installs slip in the south region last month?" Live data install jobs · outage log read ✓ Process maps install process, step 4 read ✓ Documents contractor SOP · region notes read ✓ Answer "Install SLA dropped from 96% to 88% because contractor B's crews fell behind after the storm week; step 4 (site survey) is the bottleneck." sources cited: jobs · process · SOP ✓ A question, asked as people ask it. Data, processes and documents, all read. An answer you can check, sources cited.
Grounded in your data, your processes and your documents, with its sources shown.

The full scope of a change

Ask what a change would touch and AI Insight works out everything the change affects, the way a careful architect would first. A retry on the payment step also affects the support-desk rule that fires on failure, the revenue report's pending-payments section and the portal label a customer sees, including the ones you did not think to mention. They come back as one scoped list, so the decision is made with the full picture.

  • Every affected workflow, mapping, report and portal listed before anything is built.
  • The areas you might have missed are named up front.
  • The scoped change hands straight to the AI Assistant to plan and build, with your approval at each step.
Live The full scope of a change One change · every consumer named
It knows how everything connects A proposed field change radiates through the metadata graph: mappings, two workflows, a report and a portal page light up as affected, including one nobody had thought of. Proposed change rename Customer.Status 2 field mappings billing ingress · CRM egress 2 workflows churn alert · nightly sync 1 report board pack, section 3 …and one you had not thought of customer portal: status page filter The full impact list, before anything breaks. it reads the metadata graph, so nothing is forgotten One proposed change, traced through everything. Every consumer named, including the surprise.
Ask what a change touches and get the whole list: mappings, workflows, reports, and the consumer nobody remembered.

Insight you can act on

Every answer can become the start of something. A diagnosed failure becomes a proposed fix, an explained process becomes an updated SOP, and a scoped change becomes a plan the AI Assistant builds. It runs on a hosted model or on one that never leaves your network, so the company's questions stay inside the company.

  • From answer to action: a fix, an updated document or a build plan, each one approved by you.
  • The same insight inside monitoring, processes, workflows and portals, from one assistant.
  • Your choice of model: a hosted provider, or a local one so nothing leaves your servers.
Live From answer to action Same conversation · every change proposed first
From answer to action From one conversation the copilot proposes three actions (fix the mapping, update the SOP, draft a build plan), each approved by you before anything changes. Same conversation, one line later: "Fix it." Fix the mapping survey step re-pointed to the new field proposed change approved by you ✓ Update the SOP contractor doc v5 — step 4 rewritten proposed change approved by you ✓ Draft the build plan backlog workflow + weekly report proposed change approved by you ✓ Every change is a reviewable proposal to approve or discard. nothing lands until you say yes Hosted or fully local models your data can stay on your servers The answer becomes three proposed actions. You approve each one, and then it lands.
Fix, document and plan from the same conversation, with every change proposed first and approved by you.

Keep exploring

More in Run

Know what is happening and fix it early.

The monitoring screens show records moving, jobs running, queues building and errors as they happen, and when a job fails the assistant proposes the fix.

Operations & governance →

Describe the application and the assistant builds it.

Tell the assistant what the business needs and it plans, builds, tests and promotes the tables, workflows, portal and reports, with you approving each step.

AI Assistant →

See it on your own systems.

A demo takes about an hour. Bring the failure that last woke someone up and we will show you how STRAX handles it.

Request a demo → Request a quote