Corporate Coaching & L&D

AI for Corporate Coaching & L&D

For Chief People Officers, L&D Directors, Executive Coaches, and HR Technology leaders. Our only live, in-production reference is in this sector, an AI matching system running today at bettercoach, not a pilot, not a demo.

Discuss your matching or content workflow See bettercoach ↗

The problem

Matching by hand doesn't scale, and coaching data is too sensitive to cut corners on

Matching a client to the right coach means interpreting unstructured enquiries across language, seniority, location, and topic, then searching profiles by hand. It's slow, inconsistent between operators, and constrained by real data privacy requirements that a generic AI tool doesn't respect by default.

We've already built this exact system, live, for bettercoach. It's not a hypothetical case study, it's the reference we point to first.

What we build

From unstructured enquiries to ranked, explainable matches

Matching

AI Coach Matching & Knowledge Base

Semantic search and RAG-based retrieval that match clients to coaches across language, seniority, location, and topic, from unstructured, multilingual enquiries, with every match explainable and reviewable.

Notes

Automated Session Note Processing

AI systems that structure and summarise coaching session notes, surfacing themes and follow-ups without a coach or coordinator re-reading every transcript by hand.

Analytics

Coachee Progress Tracking & Analytics

Dashboards that track coachee progress across sessions and cohorts, turning qualitative coaching notes into patterns an L&D team can actually report on.

Content

L&D Content Intelligence Workflows

AI pipelines that organise and surface the right learning content from a growing internal library, instead of a folder structure nobody fully searches.

How we deliver

Build-and-transfer, with privacy built in from the start

01

Discovery

We map how matching, notes, or content actually move through your platform today, and where privacy requirements shape what the system can and can't do.

02

Build

We build the matching or processing engine on your infrastructure, with every automated decision explainable and reviewable by a human operator.

03

Shadow-run

Your team runs the system alongside the current manual process before we step back, comparing match quality and outcomes directly.

04

Handover

Full documentation, source code, and training, so your team can operate and extend the system independently.

Case study · Live in production

Coach matching: from 7 days to seconds

bettercoach matched clients to coaches entirely by hand, reviewing enquiries, interpreting needs, and searching profiles across language, seniority, location, and topic. We built a privacy-aware matching engine combining semantic search, RAG-based retrieval, keyword scoring, and proximity signals. Every match is explainable and reviewable by a human operator. Matthias Hüthmair, Managing Director at bettercoach, described the team as handling "a topic of high complexity with great project management skills" and a "trustworthy partner" for a high-impact feature.

7 days → seconds

Matching time

Measurable

Match quality for the first time

Extra headcount to scale

Discuss this with AI:

Ready to start

Tell us what's still done by hand

One conversation is enough to scope it. Fixed-fee. Every match explainable, every note reviewable.

info@kelriva.ai

FAQ

AI for Corporate Coaching & L&D: what buyers actually ask

Do you have a live reference client in coaching?

Yes. bettercoach runs our AI-assisted coach matching engine in production today. Their Managing Director, Matthias Hüthmair, has publicly described the engagement and is available for a reference call.

How do you handle the privacy of coaching conversations and client data?

Coaching data is sensitive by nature, and the matching system was built around that from the start, privacy-aware retrieval, human review of every match, and no reliance on a generic third-party AI tool that wasn't designed for this kind of data.

Can the matching system handle multilingual enquiries?

Yes, that was one of the core requirements at bettercoach. The system surfaces ranked coach shortlists from unstructured, multilingual client inputs directly.

Can this integrate with our existing coaching or L&D platform?

Yes. We integrate via APIs and direct connections with coaching marketplace platforms, HR systems, and internal L&D tools, building around your existing platform rather than requiring a replacement.

What does an engagement in this sector cost?

Our bettercoach matching engine engagement is the closest reference point for a comparable build. Most engagements in this range fall between the £8,500 IDP Proof of Concept and the £15,000 LangGraph Agent MVP depending on scope, and every engagement is scoped and fixed-fee before work begins.