Synergised Consulting
Operations & AI insights

Insights for running a business that doesn’t need you.

Practical operations and AI insights to help your business become easier to run, and less dependent on you.

Title card: Testing An AI Agent Before It Goes Live, First 100 Days Operations
Technical asset

How Do You Test An AI Agent Before It Touches A Live Business Workflow?

Test an agent with an eval set of 20-50 tasks from real work, sandbox the tools, run it in shadow mode beside your current process, graduate autonomy on evidence, and turn every failure into a permanent regression test.

9 min read
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Title card: An Agent Has No Memory, with the supporting line What to store, what to expire, how to test it, on Synergised brand tokens
Technical asset

Your AI Agent Doesn't Have a Memory. It Has a Context Window -- And That Is the Problem

Agent memory fails quietly: context degrades answers and one poisoned write persists. What to store, what to expire, and how to test the store.

9 min read
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Title card: a 1.3B parser reads messy scans while a separate 2B checker model decides which extracted pages need human review
Technical asset

A 1.3B Model Reads Your Scans. The Interesting Part Is the 2B Model Checking Its Work

OpenBMB released a 1.3B document parser alongside a separate 2B checker that scores OCR output and flags what a human must review, and the split is what makes document automation safe near financial records.

5 min read
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Title card on a light ground with an orange rule, reading DeepSeek open-sourced the engine behind its AI service, with the line The margin is in the cache, not the model.
Method

DeepSeek Open-Sourced the Engine Behind Its AI Service. The Interesting Part Is What It Kept

DeepSeek open-sourced DeepInfer, the engine behind its own AI service, and disclosed what it earns per GPU-hour. The parts that make those economics work stayed inside the company.

5 min read
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75 per cent price rise figure beside the post title on a light title card
Proof asset

Local AI or Seat Subscriptions: The Pricing Just Moved on Both Sides

OpenAI added $100 Premium seats and NVIDIA's DGX Spark rose 75 per cent in a year. What each route costs a 25-seat firm, and the register worth building before you commit either way.

7 min read
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Title card hero for the Lovable SSR and AI visibility post, set in Synergised brand type
Technical asset

Lovable Moved Its Own Site Off Next.js. The 98.5% Figure Is the Story.

Lovable has moved its own 42-million-visitor website onto the same server-rendered hosting as its 70 million AI-built apps. The migration is engineering news; the 98.5% lift in traffic from AI tools after pre-rendering is the number owners should look at.

8 min read
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Title card: Your Agent Does Not Need a Memory Layer. It Needs Its History Back.
Technical asset

Your Agent Doesn't Need a Memory Layer. It Needs Its History Back.

A plain retrieval baseline over raw conversation history beat the tested agentic memory systems in six of seven benchmark settings, and took a fraction of the ingestion time. Measure the cheap baseline first.

6 min read
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Title card: One Box, Five Models, and a Licence Problem, with a 0.9 second measured median voice callout
Technical asset

One Box, Five Models, and a Licence Problem

LocalRouter runs chat, speech, image and video on one NVIDIA DGX Spark with a sub-second voice loop. The router is Apache 2.0. The models are not, and the licences decide what a business can ship.

8 min read
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Technical asset

The expensive model should stop typing: what the handoff research actually found

Escalating a cheap model's failed work up to a strong one recovers less than half the quality gap and multiplies cost. The favourable direction is the other way round: strong model plans, cheap model executes.

7 min read
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What gets written here

Five pillars, one question each

Method
How do data consolidation and task-specific AI agents work in an operating business?
Adviser asset
Which operational issues create diligence risk or owner dependency?
Proof asset
What data and system evidence will an acquirer need to trust?
Outcome asset
How can a founder-led business become more transferable?
Technical asset
How can AI be used safely in core workflows?