---
title: "From the first honest assessment to something that runs on Monday"
url: "https://predictes.com/services"
description: "Twelve services covering AI strategy, engineering, ontology, data, agents, workshops and managed operations — from a first assessment to a system somebody runs."
---

What we do

# From the first honest assessment to something that runs on Monday

Most AI work fails between the strategy and the system. These services are arranged along that path, and each one can be bought on its own.

-   [
    
    ## AI Strategy
    
    Which decisions are worth changing, what each would cost, and what would measurably be different. Including the ones where the answer is not AI.
    
    Read article](https://predictes.com/services/ai-strategy)
-   [
    
    ## AI Transformation
    
    The part after the strategy: sequencing against real capacity, changing how work is done, and making adoption somebody's job rather than a hope.
    
    Read article](https://predictes.com/services/ai-transformation)
-   [
    
    ## AI Agents Engineering
    
    Agents that do work rather than answer questions — with bounds, tools, approval gates and a decision log that survives the first incident.
    
    Read article](https://predictes.com/services/ai-agents-engineering)
-   [
    
    ## AI-Native Apps Design
    
    Designing software around a component that is fast, useful and sometimes wrong — which is a different design problem from anything before it.
    
    Read article](https://predictes.com/services/ai-native-apps-design)
-   [
    
    ## AI-Native Apps Engineering
    
    Turning something that works in a notebook into software your people can depend on — evaluation, retrieval, cost control and everything a prototype skipped.
    
    Read article](https://predictes.com/services/ai-native-apps-engineering)
-   [
    
    ## Ontology Design and Engineering
    
    One agreed model of your business — entities, relationships and rules — implemented so software and agents can reason over it instead of guessing.
    
    Read article](https://predictes.com/services/ontology-design-and-engineering)
-   [
    
    ## AI Data Engineering
    
    The pipelines, quality checks and lineage that decide whether an AI system is trustworthy — usually the difference between a good demo and a good system.
    
    Read article](https://predictes.com/services/ai-data-engineering)
-   [
    
    ## AI Workshops and Training
    
    Sessions built around your processes and your data. People leave with a decision or a working thing, not with notes.
    
    Read article](https://predictes.com/services/ai-workshops-and-training)
-   [
    
    ## AI Managed Services
    
    Running what has been built. Monitoring designed for systems that go wrong without an error, response times in writing, and a support tier meant to shrink.
    
    Read article](https://predictes.com/services/ai-managed-services)
-   [
    
    ## Field Deployment AI Engineering
    
    AI that works on a shop floor, in a vehicle or on a site — offline-tolerant, on hardware that survives the environment, usable by people not at a desk.
    
    Read article](https://predictes.com/services/field-deployment-ai-engineering)
-   [
    
    ## AI Agents Spec-Driven Development
    
    A development method where the specification is the artefact under version control and agents generate the implementation against it, with review where it belongs.
    
    Read article](https://predictes.com/services/ai-agents-spec-driven-development)
-   [
    
    ## AI Dark Factory Context Development
    
    The machine-readable context an unattended operation needs before it can run: state, constraints, exception handling and provenance for every decision.
    
    Read article](https://predictes.com/services/ai-dark-factory-context-development)