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Deploint

Capabilities

From architecture to production.

Seven engineering disciplines and one delivery standard. The people who design a system also build, secure, integrate and operate it.
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Capability map

07 + integration

Cross-cuttingSystems IntegrationSpans 07

Every discipline connects to the same integration layer: APIs, events, identity and data contracts.

01Capability explorer

Seven disciplines, one engineering standard.

Select a capability to see what we engineer, the reference architecture behind it and where to go deeper.

Capability 01

01 / 07

AI systems engineered for production.

Production AI systems with retrieval, agents, tool use, guardrails and evaluation, engineered into real enterprise workflows.

What we engineer

  • Agentic AI
  • Multi-agent systems
  • RAG
  • LLM applications
  • AI copilots
  • AI automation
  • Computer vision
  • Speech AI
  • Model orchestration
  • AI evaluation
  • AI governance
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Reference architecture

  1. Enterprise Data
  2. Data Processing
  3. Retrieval
  4. Models
  5. Agent Orchestration
  6. Tools
  7. Guardrails
  8. Evaluation
  9. Observability
  10. Production

01 / 07 disciplines

02Systems integration

Integration runs through everything we build.

Systems integration is not a separate practice at Deploint. It is part of every capability, because no enterprise system works in isolation.

Integration topology

05 contracts

Systems of record (ERP, CRM, Core platforms, Legacy systems, Data warehouse) and systems of engagement (Web & mobile, AI agents, Analytics, Partner APIs, Devices) connected through an integration layer of APIs, Events, Change data capture, Identity, Workflows.

Systems of record

  • ERP
  • CRM
  • Core platforms
  • Legacy systems
  • Data warehouse

Integration layer

  • APIs
  • Events
  • Change data capture
  • Identity
  • Workflows

Systems of engagement

  • Web & mobile
  • AI agents
  • Analytics
  • Partner APIs
  • Devices
  • 01

    API management

    Gateways, versioning, authentication and documentation for internal and partner APIs.

  • 02

    Event streaming

    Durable, replayable event backbones that decouple the systems producing data from those consuming it.

  • 03

    Change data capture

    Keeping systems of record and new platforms consistent without modifying legacy code.

  • 04

    Identity federation

    Single sign-on and workload identity across clouds, SaaS and on-premises systems.

  • 05

    Enterprise connectors

    Integration with ERP, CRM, MES, EHR and SaaS platforms through their supported interfaces.

  • 06

    Workflow orchestration

    Long-running processes that span systems, with retries, compensation and audit trails.

03One team

Disciplines that combine on one team.

Real systems cross discipline boundaries. A production AI assistant is also a data platform, a security surface and a cloud workload, so we staff around the system rather than the org chart.

  1. 01

    One accountable architecture

    A single technical lead owns the end-to-end architecture, with specialists from each discipline contributing to it.

  2. 02

    Security and operations from day one

    Security and platform engineers join at design time, not at the pre-launch review.

  3. 03

    A shared definition of done

    Tested, secured, observable, documented and deployable through automation, whichever discipline built it.

Disciplines involved in each concept architecture

Concept Architecture

04Go deeper

Capabilities, applied.

See how capabilities combine into structured programs, and how they adapt to the data, systems and regulatory context of each industry.

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