Primary outcome
make teams productive faster with adaptive learning
What we ship
AI coach, role-based learning paths, assessment workflows, and content refresh system
KPIs we report on
ramp time, certification completion, knowledge retention, and performance lift
What "automating training and enablement with AI" actually means
Automating training and enablement with AI is not a single product you buy. It is a workflow you redesign around AI as the operating layer. The agent handles the high-volume, high-structure tasks. Humans handle edge cases, exceptions, and trust-sensitive decisions. The system is instrumented to measure ramp time, certification completion, knowledge retention, and performance lift and improve weekly.
What changes by industry is the systems the agent integrates with, the data it retrieves over, the controls it operates under, and the KPIs it has to defend. The architecture is similar; the integration and the controls are different.
The architecture we use for AI training and enablement
- Frontier LLM — Claude, GPT-4-class, or Gemini. We benchmark candidates on a labelled test set during Discovery.
- Retrieval layer over your approved internal sources, with source citations on every output.
- Tool use for reads and writes against your operational stack (CRM, ERP, ticketing, data warehouse).
- Reviewer queue for low-confidence outputs. Confidence thresholds set per workflow.
- Evaluation harness — labelled test set, weekly accuracy reports, regression alerts.
- Versioned prompts and reviewer-action audit logs for traceability.
1 industries with a scoped engagement page for training and enablement. Each is a dedicated build with industry-specific systems, controls, and pricing.
How do you automate training and enablement with AI?+
We map your existing training and enablement workflow, identify high-volume and high-structure tasks, build an AI agent that handles those tasks, and route low-confidence cases to a human reviewer. The build connects to the systems your industry already runs on, runs against a labelled test set, and ships behind a reviewer queue before it sees production traffic. We measure ramp time, certification completion, knowledge retention, and performance lift from day one and improve weekly.
What is the best AI agent for training and enablement?+
There is no single off-the-shelf "best" agent for training and enablement — the right architecture depends on the systems and data of your industry. We typically combine a frontier LLM (Claude, GPT-4-class, or Gemini) with a retrieval layer over your approved sources, tool-use for your stack, and a reviewer queue. We benchmark candidates against a labelled test set during Discovery and pick the model with the best accuracy/cost ratio.
What does AI training and enablement cost?+
Three phases, billed separately. Discovery sprint: $6k. Build engagement: $22k–$30k. Run retainer: $3k–$5k / mo. ~$34k–$60k typical year 1 (60% take the run option for ~6 months). Pricing varies slightly by industry — see the industry-specific pages below.
How long does it take to deploy AI training and enablement?+
Thin-slice in production in ~6 weeks after Discovery, full Build phase over 7-10 weeks. By day 90, ramp time, certification completion, knowledge retention, and performance lift is instrumented and you have a baseline against which to expand to adjacent workflows.
Which industries do you build AI training and enablement for?+
1 industries listed below have a scoped engagement page for training and enablement, each with industry-specific systems, controls, and KPIs. Common starting industries include Airports, and others. Don't see yours? We build for any sector — tell us about your workflow and we'll scope it.
What do we own, and what do you own?+
We own workflow design, prompts, retrieval architecture, evaluation harness, and weekly improvement. You own data access, policy, exception approval, and final commercial decisions. At the end of the engagement, every prompt, eval, and config is handed over — no lock-in.
Selected portfolio
Real builds tied to training and enablement
A rotating selection of engagements where training and enablement was a primary driver, drawn from our active portfolio. Sectors and scope are accurate; client identities are withheld under engagement NDAs.
Q1 2026
AI pricing system for startup founders — 9-step foundation + personalised AI brain
Founder-led pricing-strategy AI SaaS · DACH
First AI-powered pricing platform for startup founders. Structured 9-step pricing-foundation flow (product, customers, competition, costs, boundaries, model, strategy), personalised AI brain that learns from each business over time, two subscription tiers with money-back guarantee. Built end-to-end including billing, AI orchestration, and onboarding.
- Next.js + TypeScript
- Multi-LLM orchestration
- Subscription billing
Q4 2025
Internal automation tool — workflow automation for consulting operations
Multi-vertical consulting group · Europe
Internal automation tool to streamline workflows, reduce manual administrative load, and improve operational efficiency across consulting and management processes. Integrates with existing systems rather than replacing them, automating handoffs and document flows that previously moved through email.
- Workflow automation engine
- Document-flow integration
- Operational dashboards
Q3 2025
Property marketplace — buy, rent, list across apartments, villas, commercial
Regional real-estate marketplace · GCC region
National real-estate marketplace covering apartments, villas, and commercial property: listing management for agencies and owners, search and filter optimised for local buyer intent, SEO foundation built for long-tail property queries, lead capture per listing with routing to the listing agent.
- Next.js + dynamic SEO routes
- Listing CMS
- Lead routing engine
Client identities withheld under engagement NDAs. Sector, geography, and scope are accurate. Full case studies on request.