AI & Automation
Def Works adds practical AI and automation to websites, mobile apps, CRM systems, and internal workflows. We focus on useful features that save time, improve support, and make business data easier to act on.
Business Dashboards
Reporting dashboards that connect sales, marketing, operations, and customer data in one place.
Workflow Automation
Automations for CRM updates, customer follow-ups, reports, internal approvals, and repeat admin work.
Chatbots & Conversational AI
Website, WhatsApp, and Slack assistants tuned for customer questions, bookings, sales, and support.
Prompt Design & Evaluation
Prompt design, test cases, and evaluation flows that keep AI responses useful and predictable.
AI Feature Operations
Monitoring, fallback paths, logging, and guardrails for AI features embedded in customer-facing products.
AI Integrations
Connect AI capabilities to your existing tools — CRMs, ERPs, document stores, and internal APIs — via clean, typed interfaces.
Every engagement includes
Technologies we use
A delivery process built for certainty
Workflow Discovery
We audit your current tools, data, and repeat tasks to identify where automation will actually help.
Solution Design
The chatbot, dashboard, integration, or automation flow is agreed before anything is built.
Build & Test
AI features and automations are built iteratively with test cases and real workflow examples.
Launch & Monitor
The system is deployed with monitoring, logs, and fallback paths so quality is maintained over time.
Frequently asked questions
Do we need a large dataset to get started with AI?
Not necessarily. Many useful automations start with your existing website content, product data, CRM notes, documents, or support history.
Which AI models do you work with?
We are model-agnostic — Claude, GPT-4o, Gemini, and open-source models like Llama. We recommend the right model for your latency, cost, and capability requirements.
How do you prevent hallucinations in production?
Grounding responses in a vetted retrieval layer, implementing output validation, and running systematic red-teaming are the core techniques we use.
Can you take over an existing ML codebase?
Yes. We begin with a code and data audit, then agree a roadmap for stabilisation and improvement before adding new capabilities.
// Let's build
Ready to get started?
Book a discovery call with our senior delivery team. We'll scope your goals and propose a practical plan.