Agentic Managed Services

Connect your team’s context and let expert agents do the work.

Every interaction compounds learning and captures the know-how nobody wrote down.

The problem

The smartest AI tools still don’t know your business.

Knowledge capture, understanding context, and continuous learning are impossible given today’s data, tools, and rate of change.

01

What’s written down is scattered.

The facts live in dozens of your systems that don’t talk. Nobody sees the whole picture.

02

How things really get done lives in people’s heads.

The unwritten rules, the patterns, the “who to ask” — new hires take years to absorb them.

03

What your best people just know walks out the door.

The hardest calls depend on a few experts’ judgement. When they go, it goes with them.

The work piles up, risk increases, and the best people spend their day on triage instead of valuable work.

42% of what an employee knows about doing their own job is never shared with a colleague.

Panopto, “Workplace Knowledge and Productivity Report,” 2018

The gap

Why this gap has been hard to close.

Every tool on the stack was built for a different job. Answering questions. Finding documents. Modelling data. Hiring people. None was built to do the work.

Generic AI assistants

Built to answer anything. Real work needs an answer solid enough to act on.

Search & retrieval (RAG)

Built to find what’s written down. The hardest calls aren’t in any document.

Even with retrieved context, 43.1% of responses in the RAGTruth corpus contained hallucinations. — Niu et al., “RAGTruth,” ACL 2024

Hand-modelled data platforms

Built for a business that holds still. The business changes faster than consultants can re-draw the map.

People and outsourcing

The only way to buy judgement. More output means more people, and the expertise never becomes the company’s own.

What’s newly possible

A system that learns an organisation’s judgement and does the work with it.

95% of enterprise GenAI pilots deliver no measurable P&L impact.

The GenAI Divide: State of AI in Business 2025, MIT, Aug 2025

The solution

The work, finished, while keeping your most valuable assets in-house.

Expert agents take the whole task: research, analysis, the draft, the recommendation. The knowledge they build stays with you, not with a model vendor. Named people still own the calls that need an owner.

Underneath the agents is the Accrete Knowledge Engine. Pointed at your environment, it builds a living map of how your organisation actually works, and keeps it current.

Knowledge Engine Platform

Ask for an outcome. Get the finished work.

The Knowledge Engine brings the conversation, connected work, and finished artifact into one visible path.

KEP

Revenue operations review

Review Q2 pipeline health by region and identify the biggest revenue risk.

I connected pipeline history, stage movement, activity, and regional targets. I’m preparing the risk brief now.

Q2 pipeline risk briefReport

58%

lower token cost

when using Knowledge Engine

2x

more tasks

vs. frontier models

32%

more accurate with open source

vs frontier model

19 of 34

tacit-knowledge facts captured

vs. RAG’s 1

Source: “Knowledge Engine Platform for Long-Horizon Professional Agents” and “Context Graphs for Recovering Tacit Organizational Knowledge”, Accrete AI, August 2026.

How it works

How it works — in three steps.

Step 01

Ground it.

Accrete points the Knowledge Engine at your environment — tickets, logs, contracts, the work people do every day. The knowledge map is standing and queryable in 2–4 weeks. No year-long integration.

Step 02

Put it to work.

Expert agents take on one painful workflow, benchmarked against your organisation’s own ground truth, with the team in the loop.

Step 03

Scale it.

Proven workflows expand across your organisation. Each one starts from the grounding the last one built.

See the work done before you commit to scale.

Select a workflow →

Proof

The proof, in numbers.

Case 01

A leading entertainment company

  • ~92%

    time savings on artist analytics (2 hours → ~5 minutes)

  • 45

    weekly reports automated

  • 87%

    faster brand-risk detection

  • 30+ years

    of content unified

Case 02

A private investment fund

  • 2 weeks → 6 min

    investor reporting turnaround

  • 500+

    investors reported on simultaneously

  • 92%

    accuracy, with zero hallucinations in reports

Case 03

A leading global P&C insurer

  • 200M+

    records reconciled into one graph

  • 1–3 months

    pilot to value (customer-deployment timeline)

After an enterprise-search deployment had already failed.

See it done.

In weeks: current-vs-future-state numbers, ready to take to leadership.

Select a workflow