Plexara
Use Cases
A Day of Analyst Work, in Twenty Minutes With Review
The work itself
Six jobs that used to need a specialist and a free afternoon
None of these are demos. Each one was a real request, answered by an agent working through Plexara, and reviewed by the person who asked for it.
Capacity planning
The peak-day capacity model
Built from live telemetry across both metric stacks and anchored to a June load test. Projected peak-day load came in near one percent of the measured ceiling: a number the client could plan against instead of a guess.
Retail engagementRelease operations
Release-day verification
A point-of-sale version rolled out wide in the middle of the season. By end of day the agent had confirmed a 99.6 percent cutover, zero ingestion gaps, and six data-integrity checks passing, with the three straggler registers identified by name.
Retail engagementRisk and fraud
Loyalty fraud scoring
Asked to examine manager-override-locked loyalty accounts, the agent scored 672 of them: risk tiers, transaction-velocity histograms against the fraud-system limit, and a worked list of the accounts worth investigating first.
Retail engagementAudience and marketing
A win-back audience in an afternoon
Expired members who were fans of one original series: 991 people, built from consented viewing data joined to the prospect feed, with hours watched and episodes per fan attached. The privacy constraint was honored in the query, not in a caveat.
Public media engagementDebugging
Root cause across the fence
Monthly analytics were missing browser users. The agent traced the gap through the pipeline to an upstream vendor intermittently dropping a required tag, and shipped the evidence queries along with the verdict: the fix belongs to the vendor.
Public media engagementData engineering
Pipeline recovery, verified
After a webhook ingestion bug was fixed, the agent inventoried all forty affected event syncs, confirmed the two-month backlog had recovered, and left a cross-reference report behind for the next person who asks.
Public media engagementTold in full
Both engagements, start to handover
Each account runs from the estate as Deasil Works found it, through the first questions and the parts that were hard, to the point where the client kept working without us in the room.
The Whole Year Comes Down to One Week
Hundreds of stores, seasonal pop-ups, and a point-of-sale platform that all have to hold through the days around one summer holiday. Every developer and analyst had wired up their own AI with their own private fixes for grounding it in truth, and progress stopped there.
- 13 governed connections behind one endpoint
- 3 storage engines joined in a single federated query
- 71 dashboards, forecasts, and audits saved in five months
Teaching the Agent Everything We Know
A regional broadcaster with more than a dozen upstream sources feeding one warehouse. Years of anomaly hunts and pipeline debugging had made the consultancy expert in every idiosyncrasy of that estate, and onboarding a new analyst still took months because the knowledge lived in people.
- 17 live connections, from the warehouse to thirteen APIs
- 1,400+ governed API operations, every call authenticated and audited
- 9 canonical knowledge pages the client now owns
Common questions
Use Cases FAQ
Two things. It uses your data through semantic catalog search, schema understanding, federated SQL, object storage, and lineage. And it invokes your APIs: OpenAPI specs imported into the gateway become governed tools it can discover and call. An agent that does both correlates what the data recorded with what your operational systems report.
Every call through the gateway is authenticated, permission-checked against the connection and persona, and logged. The agent reaches only endpoints an administrator imported, and each invocation lands in the audit log with the user, persona, endpoint, and result. Invocation stays a governed, audited action at every step.
Learn more: Governance: personas, access, and auditAs the agent works, explorations, corrections, and failures become memory. Insights are reviewed and synthesized, and approved knowledge lands in the catalog for the next session to use. A correction from an expert today becomes part of what every future agent knows, so the platform gets better the longer your team uses it.
Learn more: From memory to insights and knowledgeKnowledge describes the data and the business: what a sale is, where it lives, when the fiscal year starts. Prompts describe what to do with them: a report's sections, columns, language, and audience. When last year's ad-hoc report returns with a new dimension, the knowledge already understands the data and the prompt already carries the structure, so a project becomes a sentence.
Learn more: Prompts as reusable SOPsAn asset is one durable artifact from a session: a query result, a chart, an export, or a generated document, saved with the lineage of which tool calls and datasets produced it. A collection groups related assets into a titled, sectioned package with version history and shared comments, like a board packet or a weekly review. Together they replace the ad hoc "send a CSV in Slack" habit with governed work that persists in the portal.
Learn more: Tour the portal workspaceYes. Plexara reaches your warehouse through Trino federation, so your BI tool keeps connecting exactly as it does today. Plexara adds the governed AI agent surface on top, and analysts pick the BI tool or the agent per task. Adoption is additive rather than a migration.
Learn more: Trino Query: analytics and insightsYes. The retail and public media stories are anonymized accounts of real Deasil Works engagements. Names, specific metrics, and identifying details are withheld, but the arc is real: siloed AI, one governed connection across data and APIs, corrections that became knowledge, and a client that connected its own agents.
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Retail Use Case
A seasonal retailer whose whole year peaks in one week, and the agent that helped carry it.