Wearemaybetech

15/08/2026

🔍 How Can Connecting AI to 2,000+ Tools Transform Your Business?

Maybe* is changing the AI game via our integration with Make. You can connect to over 2,000 essential business tools, creating a seamless and powerful automation experience. 🚀

Imagine automating your workflows without writing a single line of code. With this integration, you can connect your favourite tools like Slack, Salesforce, and HubSpot, eliminating manual data entry and reducing operational friction. It's all about working smarter, not harder.

This isn't just about convenience, it's about transformation. Picture your marketing team automatically generating and scheduling social media content, or your customer service team building automated support workflows that connect multiple touchpoints. The possibilities are endless.

But the real magic happens with our multi-LLM approach, combining the capabilities of OpenAI, Anthropic's Claude, Perplexity, DeepSeek, Gemini, Mistral, Grok and Stable Diffusion. This powerhouse of AI models allows you to generate and distribute content, analyse data, and create sophisticated problem-solving workflows, all while maintaining enterprise-grade security. 🔒

The integration is live and ready to revolutionise your business processes. Whether you're looking to enhance operational efficiency or provide 24/7 customer support, AI Agents from Maybe* and Make have you covered.

Curious about how this integration can benefit your organisation? With Maybe*, it can be your reality. Get started today and learn more about how to harness the power of AI Agents in your business strategy.

https://www.maybetech.com/blog/maybe-announces-game-changing-integration-with-make-connect-your-ai-to-2000-business-tools

Discover Maybe*'s latest integration with Make, enabling seamless AI connectivity with over 2,000 business tools. Automate workflows, enhance productivity, and drive innovation with enterprise-ready security. Learn how this game-changing update can transform your business operations today.

15/08/2026

More AI tools don't necessarily lead to higher productivity. Our groundbreaking research, found in our whitepaper, "The Big AI Secret", unveils a key insight: managing more than 10 disconnected AI tools can be more of a hindrance than a help. Each tool, whether it’s Jasper for crafting content or Midjourney for generating images, introduces additional layers of complexity and hidden costs, ultimately impacting your team's efficiency and focus.

High-performing teams have unlocked the secret to true success: streamlining and integrating their tools. By selecting platforms that integrate seamlessly, they not only reduce unnecessary waste but also focus their energies on optimising workflows rather than juggling isolated tools. This strategic consolidation is key to maintaining a competitive edge and ensuring sustained business growth.

If you’re feeling overwhelmed by the sheer number of tools at your disposal, it’s time for a strategic reevaluation. Maybe* is designed to help you rethink your AI strategy, enabling you to achieve true efficiency and productivity. How many tools are you currently managing? It's time for a strategic overhaul to simplify and optimise your operations.

Explore more insights from via the link below, and discover how you can transform your AI approach today.

🔗 https://www.maybetech.com/blog/summary-tool-overload-vs-strategic-implementation-the-10-tool-threshold

14/08/2026

Enterprise AI shouldn’t require a different tool for every task, or a constant trade-off between speed, quality and governance.

That is why Maybe* has integrated a suite of leading AI models into one secure enterprise platform that can connect to your company data, and then automatically selects the most suitable model for each job. Instead of asking teams to decide which model to use and when , the platform focuses on orchestration, meaning the right capability applied to the right work, within one governed environment. It means fewer fragmented experiments and more repeatable, accountable processes.

In practical terms, this supports the work businesses do every day: drafting proposals and pitch materials, analysing large volumes of customer feedback, creating multi-channel content, and developing clear recommendations that decision-makers can act on. It also helps maintain a consistent brand voice across teams, which is often where AI initiatives succeed or fail in the real world.

Swipe through the carousel to see the headline benefits and the “AI dream team” at a glance:
✅ Faster delivery hours rather than days for common documents and content
✅ Clearer insight from customer feedback across channels themes, sentiment, prioritisation and responses
✅ More consistent quality across departments, without the manual tool-switching
✅ Stronger assurance through enterprise-ready security and SOC 2-aligned controls. Your data remains your data, and it is not used to train public models.

If you're moving from pilot projects to organisation-wide adoption, this is a practical next step: simplify the workflow, improve reliability, and scale AI responsibly.

Read the full blog below. If you found this useful, save the post and share it with the colleague leading AI security or adoption.

🔗 https://www.maybetech.com/blog/the-power-of-many-llms-how-multiple-ai-models-are-ready-to-transform-your-business

Discover how Maybe* revolutionizes business operations by integrating six leading AI models into one platform. Enhance productivity, streamline processes, and drive innovation with seamless AI collaboration. Explore the future of AI-powered business transformation today.

14/08/2026

If you're building software and you want to embed AI Agents inside your product, you should be able to do it without handing over control of the experience. The Maybe* API is designed for developers who need that level of control, whether you are integrating an agent into a customer facing app or wiring it into backend workflows.

The Maybe* Developer’s Guide walks through a straightforward path from setup to a working integration that you can harden for production. First, generate an API key in your Maybe* account by going to Settings, then Integrations, then Create API Key. Treat that API key like any other production credential, because it grants access to your account and services. Keep it confidential, store it in a proper secrets manager, and never expose it in client side code or public repositories.

Once you're authenticated, start by verifying connectivity via the account endpoint so you can confirm everything is configured correctly before you build further. From there, retrieve the user context with GET Users so your integration can stay user specific and properly scoped. Next, list available agents with GET Agents so you can select the right agent for the job and avoid hard coding assumptions. Then you can move into the core loop, create a conversation, send messages, and handle agent responses in your application or automation layer. If you want this to run reliably in production, implement sensible rate limiting and robust error handling so your system fails predictably under load. Cache static data such as agent listings when it makes sense, and keep the Postman documentation close so you can stay current as endpoints evolve.

If you're building support automation, internal ops tooling, or AI assisted analytics workflows, our guide will help you go from first request to a maintainable integration quickly. Read the full guide here:

https://www.maybetech.com/blog/how-to-use-the-maybe-api-a-developers-guide

13/08/2026

Tired of AI projects dragging on with little to show for it? Discover how to transform disarray into a competitive edge in just 12 weeks.

In a fast-paced world, many businesses find their AI programmes stumbling after a year, leaving them with little to show for their efforts. But this doesn't have to be your story. Through our comprehensive research, encapsulated in 'The Big AI Secret', we've uncovered a game-changing approach to AI implementation that defies the traditional 12-month grind.

Our proven 3-phase framework promises rapid, effective results:

1️⃣ ASSESS Weeks 1-3: Begin by gaining a thorough understanding of your current state and identifying areas of waste. High-performing organisations know that skipping this vital step can lead to costly mistakes. Instead, they streamline their assessments to ensure that every decision is data-driven and strategically sound.

2️⃣ CONNECT Weeks 4-8: Focus on creating integrations that address the most significant areas of waste. This phase isn't about adding more tools to your stack; it's about optimising the ones you already have to work seamlessly together, thus enhancing efficiency and effectiveness.

3️⃣ DEPLOY Weeks 9-12: Implement these integrated workflows across your team and diligently measure the impact. This approach enables you to achieve 2.3× faster decision-making in just 90 days, setting the stage for sustained success.

This journey is not about reckless speed; it's about smart, efficient transformation. As 'The Big AI Secret' reveals, those leading the way are the ones who act decisively, rather than waiting for the perfect conditions that may never come.

🔍 At Maybe*, we're here to support you in achieving tangible AI results. We help you build a strategic capability that not only meets your current needs but also enhances your business's bottom line for the future.

🔗 Are you ready to transition from mere experimentation to meaningful transformation? Begin your journey with us today and see the difference: https://www.maybetech.com/blog/the-ai-implementation-roadmap-from-chaos-to-competitive-advantage-in-12-weeks

Most AI programmes fail after 12 months. Learn the proven 12-week AI implementation roadmap that cuts costs, boosts ROI 3–5×, and delivers results fast.

13/08/2026

We see a familiar pattern in organisations trying to adopt AI: new tools arrive, a few pilots launch, and then progress quietly stalls.

Most of the time, the problem isn’t the tech stack; it’s the signal leadership sends about what matters. In our blog, taken from chapter 3 of our whitepaper The Big AI Secret, we share a straightforward question that predicts whether AI integration will stick: does the CEO use AI daily?

In research with 1,500+ business leaders, companies where C‑suite executives use AI every day were 1.6× more likely to achieve successful integration. When CEO-led communications clearly addressed AI strategy, that multiplier rose to 3.2×.

That gap happens because teams copy behaviour, not slogans. When leaders use AI for real work: strategy synthesis, planning, forecasting, decision prep; everyone sees it’s not optional.

When leaders communicate consistently, AI becomes a standing agenda item and a shared language across teams. When leaders remove barriers, they fund integration work (not just subscriptions), create clear governance guardrails, and invest in training so confidence grows.

If AI is treated like a toy, adoption stays shallow. If AI is treated like an IT project, it stays in IT. If AI is treated like a strategic capability, results compound across workflows.

Try the 90‑day leadership test from the post, and then take it one step further using the framework in The Big AI Secret: what did leadership say, measure, and model about AI in the last three months? Share one thing you’re doing to lead from the front, because transformation can’t be delegated and expected to work.

https://www.maybetech.com/blog/ai-success-starts-at-the-top-why-leadership-makes-or-breaks-ai-integration

12/08/2026

AI coding tools can be genuinely valuable, but only if you’re clear about the category you’re buying into.

Claude Code is often described as, “Copilot, but better”, but that’s not quite accurate.

Copilot is outstanding at inline suggestions and boilerplate speed, but it does not run your code, plan work, or complete multi-step tasks. Cursor is a strong AI-native editor that makes writing and refactoring smoother, but it is still an editor-first workflow.

Claude Code is different because it operates inside a developer’s terminal and can work across an entire codebase. It can read and write code, run tests, interpret error output, and iterate towards a working solution.

That autonomy is powerful, but it is not automatic safety.

A technically capable person still needs to brief it well, review changes, and deploy responsibly.

For leaders, the practical benefit is fewer “small but expensive” engineering hours lost to repetitive tasks and context switching.

At Maybe*, we use Claude Code and Cursor because they help us build and ship with speed and quality.

We also think it matters to say what Claude Code won’t do.

It will not chase a sales follow-up, update your CRM, or keep your project actions moving when humans get busy. That’s where Maybe* comes in: AI Agents that execute business work securely inside the tools your team already runs on. ✅

If you want the full explanation and comparison, the blog is here: https://www.maybetech.com/blog/claude-code-explained-autonomous-coding-agent

Claude Code is an autonomous terminal-based coding agent that works across a full codebase, runs tests, and iterates. See who it’s for and how Maybe* uses it.

12/08/2026

We get asked a fair question in almost every client kickoff: if AI Agents are doing the work, what are the humans for? If you're responsible for retention, you already know why this matters.

Retention isn't a one-off campaign. It's continuous observation, rapid pattern recognition, and timely intervention across thousands of customer journeys. Yet most teams are staffed, scheduled, and measured as if the work is periodic.

In part 4 of our Scaling up with Agents blog series, we explain the model we're building with groa° on Maybe*: cognitive partnership. It's not a situation where automation replaces the team. It's an environment where AI Agents take the continuous operational and analytical load, and humans take the work that compounds relationships over time. When Agents handle lifecycle state management daily, detect decay across loyalty and activation, govern suppression and deliverability, reconcile identities across platforms, and recommend channel and timing choices, the operational treadmill stops. The hours spent reconciling data and chasing inconsistencies become infrastructure that runs in the background.

That creates space for the human work that drives long-term retention. Humans can own strategy and decide which segments matter to the brand's future. Humans can shape brand meaning and creative systems so campaigns feel intentional, not rushed. Humans can design experiences that customers remember, from post-purchase to loyalty, not just optimise deliverability. Humans can also set the guardrails that keep the system safe and on-brand, including economic thresholds, voice constraints, ethical limits, and cadence ceilings. And when the edge cases arrive, a PR moment, a recall, or a culturally sensitive launch window, humans make the judgement call.

If you're exploring AI Agents, don't start with headcount. Start with the impossible part of the job, the continuous operational load. Read the blog to see how cognitive partnership changes what retention teams can deliver: https://www.maybetech.com/blog/cognitive-partnership-retention-teams-agents-groa-part-4

11/08/2026

Lots of businesses are exploring AI right now, but the real challenge is making it useful in day to day operations. Generative AI (GenAI) is being deployed widely, and a recent survey from Gartner showed how quickly it is spreading across organisations. The proportion of organisations using AI across multiple business units has grown from 13% to 28% in two years. Trust is improving too, with 75% of business units cooperating on AI initiatives.

Still, many teams get stuck after the “cool prototype” stage. Only 48% of AI prototypes move into production, and average time to production is now 8.2 months. That is where costs creep up, people lose momentum, and leaders struggle to show clear ROI.

In our blog, we outline a straightforward approach that helps teams move from experimentation to delivery. Start with a scalable AI operating model so decision making is clear and consistent. Build strong AI engineering practices so solutions can be tested, monitored, and rolled out reliably. Upskill teams with role specific AI training, and pair it with change management so people actually adopt what you build. Put trust, risk, and security at the centre so progress does not create new problems. Then use the Gartner AI Maturity Model to review your progress each year across strategy, use cases, governance, engineering and data, ecosystems, and culture.

Read the full blog now, link below. What's the biggest thing holding your organisation back right now: skills, cost, data, or getting solutions into production?

🔗 http://www.maybetech.com/blog/the-state-of-ai-adoption-in-business-navigating-the-ai-revolution

Uncover key insights and strategies for successful AI adoption in business. Explore Maybe* guidance on overcoming implementation challenges, enhancing AI literacy, and leveraging AI for competitive advantage in this dynamic landscape.

11/08/2026

OpenClaw has helped make the shift to AI ex*****on unmistakable. It shows what happens when AI Agents move from “answering” to “doing.” For individual developers, that flexibility is powerful. For organisations, it raises a different set of requirements.

In a business context, autonomy must come with control. If an AI Agent can touch tools, files, calendars, and customer systems, you need clear boundaries. You need role-based consistency so teams operate on the same rules. You need central administration to pause, schedule, and manage workflows across the organisation. You need to see what ran, when it ran, and what changed. You need an audit trail that supports accountability, not just a chat history. You also need support when workflows are business-critical.

Maybe* is built for that reality. Our AI Agents run in the cloud inside Slack or Microsoft Teams, without local installs or per-user configuration. Integrations are vetted and maintained as part of the platform. Tasks execute within defined boundaries and produce an auditable record of outcomes. That is how AI becomes operational across a team.

If you are evaluating agent tooling, start with one workflow that regularly slips. Prove value, prove control, then scale.

Read the full comparison: https://www.maybetech.com/blog/openclaw-and-maybe-governed-ai-for-business