The platform that makes custom AI repeatable.
Every Addo deployment runs on Addo Core: four layers that turn your systems, documents and know-how into agents that act, learn and stay under control. Custom for you, assembled from parts that are already proven.
A working model of how your business runs
Addo Context links the things your business deals in (customers, contracts, products, suppliers, cases) with the rules that govern them and the systems where they live. Agents reason over this model instead of raw tables, so they understand that an overdue invoice belongs to a key account with a dispute open.
- Entities, relationships and business rules in one graph
- Connectors for ERP, CRM, ticketing, data warehouses and file stores
- Permissions inherited from your source systems
- Document understanding for PDFs, scans, email and chat
- Shared across every agent you deploy
- Versioned, so changes to rules are tracked and reversible
Production agents that read, decide and act
Agents are built from tested components: document readers, planners, tool callers, software operators and reviewers. They take actions in your systems through APIs, or by operating the same screens your teams use when no API exists.
- Agent library across finance, customer, supply chain, risk and IT
- Computer-use agents for legacy and desktop software
- Multi-agent workflows with hand-offs and shared memory
- Voice, chat and email channels in many languages
- Model-agnostic: frontier, open-weight or your own models
- Human checkpoints placed where your policy requires them
Your operations become your training signal
Every approval, correction and outcome is captured. Addo Learn turns that feedback into evaluation sets and model adaptations specific to your business, so agents improve on the cases where they were weakest. Your data trains your agents only.
- Feedback capture from reviewers and outcomes
- Client-specific evaluation suites, run on every change
- Fine-tuning and preference training on your cases
- Prompt and retrieval optimization
- Regression alerts before a change reaches production
- Accuracy, cost and latency tracked per agent
Governance, oversight and cost in one place
Addo Control is where risk, compliance and operations teams see what every agent did, why it did it, and who approved it. Policies are enforced before an action runs, and every decision is logged for audit.
- Approval gates by action type, value and risk
- Full trace of inputs, reasoning steps and actions
- PII detection and redaction
- Model routing and spend limits
- Role-based access and single sign-on
- Deploy in your cloud, on premises or in Addo's managed cloud
Addo Core grows out of real deployments. Every component in it has run inside a client's business first.
Your data, made agent-ready.
Most enterprise AI stalls on data that is siloed, ungoverned and impossible to trace. Addo Context sits on top of the systems you already run, so agents share one governed picture of the business and every decision can be explained.
No migration, one semantic layer
Addo Context connects to ERP, CRM, ticketing, warehouses, lakes and file stores where they are, and maps entities, relationships and rules across them. Data engineering and governance are where Addo started, and it shows here.
Agents get the same permissions as people
Each agent has explicit, auditable rights over what it can read, write and reason from, inherited from your source systems. Adding agents tightens control instead of loosening it.
Every answer shows its sources
Decisions record the data they used and the policies applied at the time, so an auditor or a regulator can follow any outcome back to its inputs.
Knowledge compounds: what one agent learns about a customer, a contract or a process is available to the next, within the permissions you set. Data foundations as a solution →
Any model. Your choice, per task.
Addo Core is model-agnostic. Agents are built against the context and control layers, not against one vendor, so the model behind each task can change without rebuilding the agent.
OpenAI, Anthropic, Google and others through their enterprise APIs, with your data never used for training.
Llama, Mistral, Qwen and similar models run inside your cloud or on premises, for data that cannot leave.
Models fine-tuned on your cases through Addo Learn, or models your team already maintains.
Addo Control routes each task to the model that meets its accuracy, latency and cost targets, and caps spend per agent.
How the layers fit together.
Your systems feed Addo Context. Agents act on that context and write back to your systems. Addo Learn closes the loop, and Addo Control governs every step.
Runs where your data has to stay.
Many of our clients work under data residency rules across Asia, Europe and the Middle East. Addo Core is built to deploy close to the data.
Deploy in your VPC
Addo Core runs inside your AWS, Azure or Google Cloud account. Data never leaves your perimeter.
Air-gapped options
For regulated and public-sector clients, run the full stack on your hardware with open-weight models.
Addo managed cloud
The fastest start. Regional hosting, single-tenant isolation and our operations team on call.
Frontier, open-weight or your own models, routed per task. Model optionality →
Client data is never used to train models for other clients.
SSO, role-based access and permissions inherited from source systems.
Every agent action logged with inputs, reasoning trace and approver.