Oumi is your AI Factory production line. It builds, deploys, learns and compounds your own AI to your advantage.
Rent what’s generic. Own what differentiates you, what costs you most, and what you must control.
Resolves routine cases using your policies and customer context. Learns from agent corrections.
Faster resolution · fewer escalations · lower cost per resolution
Routes each task to the lowest-cost eligible model that clears quality and policy gates.
Lower inference cost · stable quality · fewer manual routing rules
Runs quantized models on the device for low-latency, private banking interactions.
Faster response · less cloud spend · more customer data kept on-device
Scores each transaction and routes the highest-risk cases for review. Learns from disputes and confirmed outcomes.
More fraud caught · fewer false declines · focused review capacity
Combines bureau, income, identity, and policy data to recommend a decision and loan terms.
Faster decisions · consistent pricing · better-calibrated credit risk
Extracts financials and applies credit policy to prepare a cited recommendation for human approval.
More underwriting capacity · faster decisions · more consistent risk grades
Assesses the business, owners, website, and processing history to set onboarding controls and monitor risk.
Faster onboarding · fewer avoidable losses · earlier risk detection
Builds a supported narrative draft from alerts, transactions, KYC records, and investigator notes. Flags missing facts.
Less drafting time · stronger evidence traceability · more consistent QA
Screens employee trading and communications against restricted lists and information barriers. Routes exceptions for review.
Faster pre-clearance · focused compliance review · stronger audit trail
Finds the policy language, endorsements, exclusions, and rules that apply. Builds a cited review summary.
Faster coverage review · more consistent analysis · stronger audit trail
Extracts risk details from broker emails, ACORD forms, and loss runs. Flags gaps and appetite mismatches.
Faster intake · fewer incomplete submissions · more underwriter time for risk
Ranks claims for SIU review and connects shared people, devices, providers, and payments across claims.
Better-prioritized SIU queues · faster evidence assembly · fewer low-value referrals
Matches patient records against versioned trial criteria and cites the evidence for human screening.
Faster screening · more eligible candidates surfaced · less manual chart review
Recommends codes supported by the clinical record. Flags documentation gaps, modifier issues, and payer edits.
Faster coding · fewer preventable denials · lower manual review
Finds payer requirements, matches them against the patient record, and flags missing clinical evidence.
Fewer information loops · faster submission · less administrative work
Flags early signs of degradation and prioritizes maintenance by failure risk and operational impact.
Less unplanned downtime · better maintenance timing · focused technician effort
Inspects images and sensor signals for visual and structural defects. Routes uncertain cases to human inspectors.
Earlier defect detection · fewer escaped defects · lower inspection effort
Optimizes job sequence around demand, capacity, materials, labor, maintenance, and changeover constraints.
Higher on-time delivery · better capacity use · fewer costly changeovers
Forecasts price movements using supplier, market, inventory, demand, and competitive signals.
Earlier buying decisions · better inventory planning · less margin erosion
Estimates incremental response and recommends the offer, audience, channel, and timing.
More incremental revenue · lower discount waste · better offer timing
Ranks products for each customer and context using behavior, catalog, inventory, and real-time signals.
Higher conversion · larger baskets · more relevant product discovery
Routes each request across a model portfolio using quality, cost, latency, policy, and fallback rules.
Lower inference cost · resilient fallback · enforced quality thresholds
Separates product regressions from stale tests, proposes repairs, and validates changes in CI.
Faster CI recovery · less engineering triage · faster merges
Scores renewal and expansion risk using product usage, support history, account context, and customer outcomes.
Earlier churn warning · focused CSM effort · better expansion forecasts
A working session with our team. You bring the problem, we build a model against it, and lunch is on us.
A generic model you rent offers no differentiation. It’s expensive at scale, unpredictable, and ultimately outside your control. The winning AI strategy is specialized intelligence you own, built for your business, outperforming frontier models on the tasks that matter, at a fraction of the cost. Oumi automates the entire AI lifecycle, giving you full transparency, flexibility, and ownership.
Industrialized model building
What Claude Code did for software development, Oumi does for AI model development. Evaluation, data synthesis, training, and deployment run automatically from a plain-English description of the task. Your ML engineer builds 100× faster. Your domain expert can build a model.
Built to give you superpowers →Cost
A specialized model is 10× to 100× smaller than frontier AI, yet matches or exceeds frontier performance on your task and serves inference for a fraction of the cost. DMG cut theirs by 100×.
Run your numbers →
Up to 50% higher quality
A specialized model trained on your task, your workflow, and your edge cases beats one trained on the public web. DMG went from 72% to 99% validation accuracy.
General loses. Specialized wins →No black box
Every evaluation result, every training example, and every recipe is inspectable and editable. Trace a behaviour back to the data that caused it; change any recipe before it runs. Full governance and auditability.
Look inside the model →AI sovereignty
Own the weights, the data, and the recipes, and run them anywhere. No deprecation notices, no pricing changes that break your budget, no quiet updates that degrade your results. Train, deploy, and improve in our environment or inside yours.
Owners compound. Renters don't →Deploy anywhere
Deploy in one click to Oumi’s GPUs that scale with your traffic: zero when it stops, hundreds when it surges. Or deploy in your own infrastructure. Frontier AI only runs in someone else’s cloud. A specialized model goes wherever you need it: a smartphone, an embedded device, your VPC, on-prem.
See deployment options →The compounding flywheel
Production signals feed back into training automatically. Failure modes get found, turned into training data, and retrained on a cadence you control. You are not maintaining a model. You are building an asset.
It closes itself →Real models, in production, with the numbers their teams measured.
84.5% → 88.9%
“Oumi enabled us to rapidly develop a specialized model for clinical text that delivers high-precision word sense disambiguation, something general-purpose LLMs struggle to achieve.”
Murali Minnah · Strategy Officer, Wired Informatics
Watch the on-demand interview72% → 99%
invoice validity, at 100× lower cost
“I'm convinced our future is to have our own fine-tuned models. The results have only gotten better.”
Kumar Srinivasan · Chief Product Officer, DMG
$10 → $0.10
per claim classification
“The accuracy has to be near deterministic. Our policy rules don't change based on what the model ate for breakfast.”
Claims Operations Lead · national insurer
52% → 83%
voice authenticity, in 73 minutes
“Oumi enabled us to take our proprietary data and easily create and run custom evaluations on any model. We were also able to start training on our data in minutes.”
Vedad Šoše · CTO & Cofounder, Original Voices
Sonnet 4.5 → Qwen3 8B
+8% coverage, +12% groundedness, at a fraction of the cost
“A research agent that hit cost and latency walls on frontier models, replaced by a custom 8B model approaching Opus-level quality.”
Aurasell
9.4K
GitHub stars, growing daily
“9,400+ developers have starred, forked, and built with Oumi.”
Open source · Apache 2.0
1,690
members in the Oumi Discord
“Practitioners building with Oumi, in the open.”
Community · discord.gg/oumi
Built by 20+ researchers from Google, Apple, Meta and Microsoft.
The State of
Owned AI
Which AI should you own
Where enterprise AI creates proprietary data, measurable value, and a learning advantage.
600+
AI decisions mapped
300+
external proof points
39
real-world implementation stacks analyzed
13,700+
senior leaders represented
15+
benchmarks audited
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