At Stride IT Solutions, we work on digital transformation for businesses of all sizes — and a big part of that means figuring out which AI tools genuinely hold up under real workloads, not just demo conditions. Here's a transparent breakdown of the stack we've settled on in 2026 and the technical reasoning behind each choice.
Why We Split Between ChatGPT and Claude
The most common question we get: why run two LLMs? The answer is context window size and task type.
Claude is our default for anything involving large documents — full contracts, lengthy reports, big datasets. Its context window handles inputs that would cause other models to truncate or hallucinate filler. For structured outputs like business proposals or content strategies where accuracy genuinely matters, Claude consistently outperforms on nuanced detail.
ChatGPT earns its place for shorter-form, iterative work — first drafts, brainstorming, summarising moderate-length documents, and handling image inputs. The custom GPT feature is worth noting architecturally: you can build task-specific assistants without touching an API, which is useful when handing tools to non-technical team members.
Both have generous free tiers. Paid plans run around £15–16/month each — we treat them as complementary rather than competing.
Make as the Orchestration Layer
Make is where the actual automation logic lives. Rather than writing webhook handlers or cron jobs for every client integration, Make lets us wire together Gmail, Shopify, Google Sheets, CRMs, and WhatsApp notifications visually. A typical workflow: form submission triggers CRM record creation, confirmation email dispatch, and an internal Slack or WhatsApp alert — no backend code deployed.
For most small business use cases, this runs comfortably within the ~£9/month tier. The ROI argument is straightforward: if it replaces 3–5 hours of manual work per week, it pays for itself in the first hour of the first month.
Perplexity for Research, ElevenLabs for Audio
Perplexity fills a specific gap: sourced answers rather than a ranked list of URLs to manually parse. When we need current regulatory information — UK GDPR rules, shipping requirements — Perplexity returns direct answers with citations, which is faster and more auditable than a standard search workflow.
ElevenLabs handles voiceover production for client video content. The quality is genuinely indistinguishable from studio recordings, and at around £4/month entry point, it eliminates recording sessions entirely for explainer and tutorial content.
The Implementation Order Matters
We always recommend starting with Claude or ChatGPT for one week on real tasks before touching automation. Once the LLM interaction feels natural, adding Make to automate one concrete process is the right second step. Layering too many tools simultaneously slows adoption.
If you want the full reasoning behind this stack and how we assess which tools fit which operations, we wrote a detailed version of this breakdown for a small business audience over at Stride IT Solutions — worth reading alongside this if you're advising non-technical clients on implementation.
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