Solutions
Use cases solved end to end
Each solution takes one business problem from your data to a business action and measures what that action returned. It predicts or detects, decides through a policy your team sets, acts inside the system your team already works in, and proves the incremental result against a holdout. Metis runs it in your cloud, on-prem, or dedicated.
How every solution works
From prediction to measured return
The model's output never touches the business directly. Every solution follows the same four steps, and each step is visible to the people who own it.
- 01
Predict or detect
A model trained on your own history scores, forecasts, or flags, with the reasons shown beside every result.
- 02
Decide through a policy
Thresholds, budgets, caps, eligibility, and approval gates sit between the score and the world. Your team sets them, and the policy, never the model, enforces the rules.
- 03
Act where the team works
Tasks, queues, orders, and decisions land in the CRM, ERP, CMMS, case management, or claims platform your people already use.
- 04
Measure the increment
A holdout, a champion and challenger, or a phased rollout shows what the action added, and the result is stated as a return on investment (ROI).
You cannot have AI, or intelligence, without data availability. Every solution starts from the data its decision needs, and every pipeline passes schema, leakage, point-in-time, and entity-resolution checks before it reaches production.
Why it holds up
AI you can invest in, not a roll of the dice
Orama designs, trains, and ships AI with you. Every solution on this page is built the same way, and that way is what makes its return something you can plan on.
Models that learn from your data
The point of AI is that it learns from data. Each solution trains models on your own data and history, rather than putting a prompt in front of a general-purpose model, so what it learns is specific to your business. Your data and the models trained on it stay yours, and you hold the source: an advantage that lasts because no one else has it.
A river of signal
Designing an AI system is like shaping a river. Each stage filters out noise and distills signal, until what comes out the end is clear enough to drive one specific decision. Checks sit at every stage, and every pipeline passes schema, leakage, point-in-time, and entity-resolution checks before it reaches production.
Framed by the outcome from the start
Many AI projects begin as experiments and hope for a result. Each solution here starts from a business outcome and works back to the data. Every link in the chain from data to outcome is an assumption, and each one is tested, so the outcome and its return can be measured.
A repeatable playbook, walked with you
Every solution follows the same playbook, and our forward-deployed engineers walk it with your team as partners. The solution is delivered and owned inside your company, without building an AI and data-engineering division first, and Orama Studio gives your team the tools to run and extend it themselves.
Measured prediction shows the drivers
Because each model's predictive power is measured, its drivers can be trusted: what actually moves churn, lifetime value, or whichever metric you run on. Once you know the drivers, you can go and fix them.
Better decisions, made quickly and at scale
An organization acts more intelligently when its decisions are higher in quality, made faster, and made at scale, many at once. That holds for the whole company and for each unit in it, and the Corporate Intelligence Capability (CIC) score on the journey pages measures it.
The catalog
Solutions by business function
Each solution is one use case, owned by one team, wired to one system of action, and measured in one business metric.
Revenue and customers
Keep and grow customers, and put marketing spend where it returns, with every contact earning its place.
- Churn & RetentionFind the customers likely to leave, act on the ones a contact can keep, and measure the revenue kept.See the solution
- Customer Lifetime ValueAllocate acquisition, retention, and promotion spend by long-term customer value, with the incrementality to prove it.See the solution
- Marketing Mix ModelingEstimate what each marketing channel really returns, and move budget within the limits your team sets.See the solution
- Automated OutboundOutbound that contacts the people worth contacting, says what the data supports, and stays inside the contact rules.See the solution
- Next-Best-ActionOne decision layer across every channel that picks the action, including no action, with the most long-term value for each customer.See the solution
Sales and pricing
Put sales effort where it converts, and quote prices and bids that hold up.
- Lead & Opportunity ScoringPut sales attention on the leads and deals most likely to convert, and measure conversion per rep-hour.See the solution
- Automatic QuotingFast, consistent quotes that are defensible rather than guessed, for your estimators and for customers quoting themselves on your website.See the solution
- Construction Estimating & Bid IntelligenceQuantities taken from drawings, coordination errors caught before bid, and a clear view of which bids to pursue.See the solution
- Freight & Supplier QuotingRead quote requests and supplier offers from email and PDF, and draft the quote, award, or counter for a person to approve.See the solution
Finance and performance
Recover cash, stop overpayments, bill for every piece of work, and explain the metrics the business runs on.
- Collections PrioritizationRecover more delinquent receivables at lower cost and lower complaint risk, with the contact rules enforced by policy.See the solution
- Recovery AuditFind and stop overpayments: freight invoice errors, duplicate supplier payments, and prices that break the contract.See the solution
- Revenue Leakage DetectionFind work that was delivered but never billed, and add the charge with the evidence behind it.See the solution
- KPI Anomaly & Driver AnalysisWhy a metric is moving, what to change, and whether the change worked, brought to a decision forum with a log.See the solution
Operations and supply chain
Match stock to demand, keep promises to customers, and make more good units.
- Demand ForecastingItem and location forecasts your planners can trust, with ranges, coherent from item to network.See the solution
- Replenishment & Inventory ActionPurchase, transfer, and safety-stock actions computed from the forecast and released under the autonomy you set.See the solution
- Delivery Date PromiseShow a delivery date customers can rely on, before they buy, and warn them before a delay.See the solution
- Scrap, Yield & Process OptimizationLearn which process settings make good units, recommend them, and catch defects on the line before they ship.See the solution
- Warranty & Field-Quality Early WarningSpot an emerging field-quality problem in technician notes and claims, and open an investigation early.See the solution
Field service and workforce
Put the right people and parts in the right place, and keep equipment running.
- Predictive MaintenanceFix equipment just before it fails, with alerts that become scheduled work orders with parts allocated.See the solution
- Field-Service Dispatch & First-Time FixThe right technician, with the right part, at the right time, so more jobs are fixed on the first visit.See the solution
- Labor Forecasting & Shift SchedulingForecast demand interval by interval and build rosters that meet it, inside labor rules and staff availability.See the solution
Risk, fraud, and claims
Stop losses in flight and route every claim to its right path.
- Fraud & Financial-Crime DecisioningStop fraud in flight while approving good customers, decided inside the authorization window and audited decision by decision.See the solution
- Claims Triage & Fraud ReferralEvery claim on its right path from first notice, with payment automated where it is safe and denial never automated.See the solution
Proof
What you see: the ROI readout
Every solution produces the same readout, assembled from the system's own records rather than built by hand.
Correctness
The checks the pipeline passed on your own data: leakage, point-in-time, and entity resolution.
Incrementality
The incremental effect against the holdout or equivalent design, with its confidence interval.
Return
The measured return against the investment, set beside the return model agreed before work started.
Guardrails
Complaints, cost, margin, fairness, and contact limits, each shown against its bounds.
Audit extract
Every score, action, and outcome, with the model and policy versions behind it.
Start with one decision
Bring the problem and the systems your team works in. We scope the first solution with you, agree how its return will be measured, and run it in production with your people.