PROGRAM
LLM & GenAI systems
Chat, copilots, RAG pipelines, and content systems grounded in your data.
- Production-aware
- Reviewed with evidence
AI Development
We build production AI systems, end to end.
From architecture and data pipelines to deployed, monitored models, Omdena ships custom AI that performs in the real world, and every commit is verified against scope by our Umaku platform.
600+
AI solutions delivered
End to end
Architecture through monitoring
VERIFIED DELIVERY
Scope, Code quality, DevOps, Bugs — reviewed on every commit, with evidence.
What we build
The full surface area of modern AI.
PROGRAM
AI agents & automation
Autonomous agents and multi-agent pipelines that take real action.
- Production-aware
- Reviewed with evidence
PROGRAM
Computer vision
Detection, segmentation, classification, and geospatial vision at scale.
- Production-aware
- Reviewed with evidence
PROGRAM
Predictive & classical ML
Forecasting, scoring, recommendation, and time-series models.
- Production-aware
- Reviewed with evidence
PROGRAM
Data & ML engineering
Pipelines, feature stores, data contracts, and the infrastructure ML runs on.
- Production-aware
- Reviewed with evidence
PROGRAM
MLOps & deployment
CI/CD for models, observability, retraining triggers, and production monitoring.
- Production-aware
- Reviewed with evidence
PROGRAM
Edge & embedded AI
Optimized models for devices, IoT, and bandwidth-constrained environments.
- Production-aware
- Reviewed with evidence
PROGRAM
Evaluation & safety
Eval harnesses, evals-driven development, and safety reviews built into delivery.
- Production-aware
- Reviewed with evidence
Technical depth
A reference architecture, not a black box.
We design for production from day one — observable, evaluable, and built on a stack your team can own after handover.
WHAT THIS MAKES PRACTICAL
PythonPyTorchLangGraphvLLMpgvectorRayKafkaKubernetesTerraformMLflow
FLOW - assess - build - embed
01
Scope
Umaku captures structured scope; team and stack confirmed
02
Build
Vetted engineers build against the documented scope
03
Review
Four AI agents check scope, quality, DevOps, bugs per commit
04
Deliver
Documented, provably-complete handover your team can own
Use cases
What teams come to us to build.
Internal copilots
LLM tools embedded in your product or workflow, grounded and evaluated.
Prediction systems
Forecast demand, detect risk, score customers, or classify at scale.
Vision pipelines
Detection, segmentation, and monitoring from imagery or video.
Agent automation
Autonomous pipelines that monitor, decide, and act without manual intervention.
Data platforms
The ML infrastructure a team needs to train, serve, and iterate fast.
Domain AI
Sector-specific systems for healthcare, agriculture, energy, and more.
A simplified process, powered by Umaku
Explore the platform Five steps from scope to verified delivery.
01
Scope
Umaku generates and maintains structured scope documentation for the engagement.
02
Build
A vetted squad builds the system against the documented scope with live monitoring.
03
Review
Four AI agents review every commit — scope, quality, DevOps, bugs — with evidence.
04
Verify
A dedicated QA pass confirms delivery completeness before handover.
05
Deliver
Documented, provably-complete handover your team can own and operate.
Outcomes
Capability that stays in the building.
Applied
People practice on real AI workflows instead of passive slideware.
1 project
A real deliverable your team owns, produced during the program itself.
In-house
The workflow, tooling and judgement to keep building after the engagement ends.
Related case studies
All
Geospatial AI · EnergyIdentifying Optimal Microgrid Sites with AI & GIS
Combining satellite imagery, demographic, and infrastructure data to prioritize rural electrification investments.
Read case study
Computer Vision · HealthBattling Malaria in Liberia with AI
Smart diagnostic and surveillance tools supporting field workers in low-connectivity environments.
Read case study
NLP · Public SectorAI to Combat Misinformation & Disinformation
Multilingual NLP pipelines that detect coordinated narratives and surface verifiable signals.
Read case study
Predictive ML · MobilityShort-Term Traffic Congestion Prediction
Spatio-temporal models that forecast congestion and inform city operations in near real time.
Read case studyHow much does it cost to move from an AI prototype to a production-ready system?
Costs depend on workflow complexity, integrations, infrastructure requirements, monitoring needs, and long-term support. Smaller team deployments may start lower, while organization-wide AI systems require broader implementation support.
Why do many AI prototypes fail after initial testing?
Many AI prototypes work well in controlled demos but struggle when introduced into everyday workflows. Common issues include unstable outputs, weak integrations, limited monitoring, scaling challenges, and unclear ownership.
Can Omdena work with our existing AI tools or internal team?
Yes. Omdena often works alongside internal engineering or AI teams to help expand, stabilize, integrate, and improve existing AI systems.
What happens after the MVP or PoC stage?
After the MVP stage, organizations often need workflow validation, integrations, monitoring, evaluation, security controls, human review workflows, and long-term maintenance support.
How long does it take to move beyond an AI MVP?
Timelines depend on implementation scope, integrations, infrastructure complexity, and rollout requirements. Focused deployments may take a few weeks, while larger cross-functional systems may require longer implementation timelines.
How does Omdena reduce AI implementation costs?
Omdena reduces implementation overhead through structured delivery workflows, deployment-focused QA, a proprietary agentic AI platform, and a vetted global AI talent network.
Does Omdena support long-term AI maintenance and monitoring?
Yes. Omdena supports ongoing monitoring, evaluation, maintenance, infrastructure management, and long-term AI usage across teams.
What industries does Omdena work with?
Omdena supports organizations across healthcare, climate, energy, logistics, agriculture, finance, insurance, mining, public sector, and other operationally complex industries.
Have a system in mind? Let's scope it.
Get a technical consultation — usually within one business day.
Get a Consultation