Custom AI
Development
Build AI into real business software with custom applications, agents, knowledge systems, document workflows and automation designed around your data, processes and users.
- Software engineering since 2004
- Custom Built Solutions
- Full stack Development
- Private + cloud AI
AI Built For The Business
Move Beyond Generic AI Tools and Build AI Into The Work Itself.
AI becomes significantly more useful when it understands the right business context, works with your data and connects to the systems your team already uses.
Seed develops custom AI applications that combine models with software, databases, knowledge sources, permissions, APIs, business rules and user interfaces.
Solutions can use private local models, commercial AI APIs, hosted models or a hybrid architecture based on the security, performance, control and capability requirements of the project.
Custom AI Capabilities
Build AI Around Practical Business Tasks
We focus on AI that performs useful work, improves access to information and becomes part of a larger business process.
Agents
AI Agents
Create specialized agents with instructions, tools, permissions, knowledge and access to approved business systems.
Knowledge
Knowledge and Search
Connect AI to documents, databases and knowledge sources so users can find and work with business information more effectively.
Documents
Document Processing
Extract, classify, summarize, organize and route information from documents, messages and other unstructed content.
Automation
AI Workflow Automation
Use AI inside larger business workflows for review, routing, analysis, approvals, service processes and automation.
Applications
AI Enabled Applications
Build complete business applications where AI is integrated directly into the user experience and application logic.
Models
Model Integration
Connect local models, hosted models and commercial AI APIs based on the capabilities and requirements of the application.
AI + Software Engineering
Production AI Requires More Than A
Model.
A useful AI system needs software architecture around the model to manage data, users, security, tools, integrations, business rules and real world workflows.
01
Business Context
Give the AI access to approved documents, records, databases and application context needed to perform the task.
02
Tools and Actions
Allow AI workflows to call APIs, search data, use MCP tools and perform controlled actions inside connected systems.
03
Security and Permissions
Control which users, agents and applications can access specific information, tools and business functions.
04
User Experience
Build AI into practical interfaces that help employees, customers and partners complete real tasks instead of simply exposing a chat window.
Our Process
Start With The Business Problem, Then Choose The AI Architecture.
The model should be selected around the job it needs to perform, the information it requires and the environment in which it will run.
01
Use Case Discovery
Define the business problem, users, available data, current workflow and expected result.
02
Architecture
Determine model strategy, privacy requirements, knowledge architecture, integrations and infrastructure.
03
Prototype
Test the workflow and model behavior with representative business information before committing to the full application.
04
Application Development
Build the interface, APIs, integrations, permissions, data connections and production workflow.
05
Evaluate and Improve
Measure output quality and refine prompts, retrieval, tools, models and software behavior over time.
Software Engineering Foundation
AI Development Backed By Full
Stack Software Engineering.
Seed approaches AI as part of a larger software system. We combine models with applications, databases, APIs, knowledge sources, authentication, permissions and business workflows to create solutions designed for real production use.
Full Stack
Application + AI Development
Flexible
Private, Cloud or Hybrid Models
Integrated
Data, APIs and Business Systems
Frequently Asked Questions
Custom Ai Development Questions
Yes. We can build the complete application around the AI, including user interfaces, APIs, databases, authentication, knowledge systems, workflows, integrations and model access.
Yes. We can design solutions around local models when privacy, data control, network requirements or deployment preferences make private AI appropriate.
Yes. AI applications can connect to existing software, databases, APIs, document systems and MCP servers when appropriate integration methods and permissions are available.
No. The model strategy depends on the application. We can work with commercial AI APIs, hosted models, private local models or hybrid architectures.
Yes. AI can be connected to controlled tools, APIs and workflows that allow it to retrieve information or perform approved actions based on defined permissions and business rules.
Start a Project
Have an AI use case that needs real software around it?
We can help define the architecture, select the right model strategy and build the software, integrations and workflows required to put AI into production.