Beyond Launch: The Scaling Series(1 of 5)
You’ve built a solid service business. Revenue is steady, clients are happy, and your use cases are proven. Now, you’re looking to scale. Shifting from people-powered delivery to a tech-enabled product: a smart dashboard, a recommendation engine, a marketplace layer, or even a personalised health platform.
But just as you start mapping the architecture, something unexpected comes up:
“We know what we want to build, but we can’t get the data.”
Whether you’re working with wearables, CRMs, social platforms, or aggregators, access to high-quality, scalable data becomes the first bottleneck. Often, it’s the dealbreaker. Especially for SMEs, non-profits, or mission-driven businesses, this part is overlooked until it’s too late.
Why Data Bottlenecks Matter
It’s rarely about a lack of data. There’s more of it than ever. What gets in the way is control, cost, and complexity. We’ve seen the same blockers appear across industries:
- Closed or premium APIs from dominant platforms
- Third-party vendors turning data into a competitive moat
- Poor interoperability or non-standard formats
- High engineering lift for in-house data pipelines
- Legal and ethical ambiguity around usage
Even the smartest product ideas can stall if the data layer is inaccessible or unstable.
Four Practical Paths to Data Access
At Teckollab, we help founders and purpose-driven teams unlock critical data—ethically, securely, and sustainably. Accessing the right data at the right time can determine whether your MVP proves a concept or misses the mark. But getting there isn’t always straightforward. APIs change. Platforms close access. Terms shift.
Here are four pragmatic strategies we’ve used with real teams to help them navigate this early and evolve with confidence:
1. Leverage Third-Party Aggregators
Identity verification providers like Yoti, OneID or social media aggregators (e.g., Ayrshare) offer aggregated access to financial, employment, and user activity data across multiple sources via a single integration.
Why it works:
- Speeds up MVP validation with plug-and-play functionality
- Reduces initial engineering lift
- Easy way to test assumptions without reinventing infrastructure
Things to watch:
- Limited control over data granularity or frequency
- Potential vendor lock-in as you scale
- Usage-based costs can grow quickly
Use when: You’re validating your idea fast and need a reliable source to demonstrate value quickly, especially in fintech, HRtech, or creator economy tools.
2. Tap into Open SDKs & Alternative Devices
When dominant platforms (e.g., Apple Health, Fitbit, Meta) restrict access, alternative SDKs, lesser-known hardware, or open-source communities can offer a backdoor to innovation—especially in healthtech, IoT, and wellness.
Why it works:
- Grants more control over data pipelines and UX
- Enables faster experimentation in R&D phases
- Aligns well with open-source, privacy-first products
Things to watch:
- Requires deeper technical skill and ongoing maintenance
- Some open tools may lack long-term support
- Device fragmentation can impact data consistency
Use when: You’re building for a niche user group or emerging tech and want more flexibility in how data is captured, processed, and stored.
3. Build Internal Data Pipelines
When external options don’t align with your roadmap or when compliance, customization, or differentiation matters building your own data pipelines gives you full control over what you collect, how you process it, and where it’s stored.
This could involve scraping, direct integrations, background processes, or orchestrated ETL workflows.
Why it works:
- Full ownership of IP and data infrastructure
- Enables deeper customisation for AI/ML use cases
- Long-term asset as your product scales
Things to watch:
- Slower to build and maintain
- Requires dedicated data ops or engineering support
- Higher upfront investment
Use when: You’re solving a unique problem, need full visibility, or want to build defensible tech around proprietary data.
4. Form Strategic Data Partnerships
Sometimes, the best data doesn’t come from APIs. It comes from relationships. Collaborating with aligned organizations, non-profits, research groups, or even regional start-ups can unlock access to high-quality, exclusive, or underutilized datasets.
Why it works:
- Creates long-term, differentiated access
- Aligns incentives beyond just technical integration
- Strengthens your ecosystem and mission
Things to watch:
- Legal and compliance reviews take time
- Requires patience and trust-building
- Often informal or undocumented
Use when: Your product is mission-driven or entering a niche market where warm intros and aligned purpose matter more than cold API calls.
From Scrappy to Scalable: An Iterative Path
You don’t need perfect data on day one. In fact, most of our clients start with what’s available and evolve their approach over time. Here’s a proven path we often recommend:
- Phase 1 – Start Fast: Use aggregators or open tools to validate core value. Build quickly and learn.
- Phase 2 – Go Deeper: As traction grows, begin forming data partnerships and refining access pathways for richer insights or better control.
- Phase 3 – Own It: When the time is right, invest in your own infrastructure. This sets you up for long-term growth, AI adoption, and deeper differentiation.
How We’ve Tackled This at Teckollab
We’ve supported early-stage founders and social impact ventures navigating these challenges across sectors:
- Identity Verification Used a combination of Open Banking APIs and wallet integrations to create compliant, user-friendly KYC flows.
- Health Data Leveraged open SDKs and alternative wearables when top-tier providers blocked granular access – enabling real-time tracking and analysis for wellness platforms.
- Localized Compliance Integrated with regional vendors of each country from EU to ensure regulatory processes and requirements are aligned to county specific requirements.
- Social Media Analytics Chose sustainable third-party APIs over deprecated open libraries to ensure ongoing access and avoid sudden deprecation risks.
Bottom Line: Make Trade-offs, Intentionally
Every approach comes with trade-offs. The key is to choose them intentionally, based on where you are in your journey—and where you want to go. At Teckollab, we partner with teams not just to ship faster, but to build more resilient, ethical, and scalable foundations for the long run.
Data access should enable innovation, not stand in its way. If you’re ready to scale, but the data feels out of reach, you’re not alone. This challenge is real, but solvable with the right strategy and support.
Let’s explore what your product needs and find the smartest way to unlock it—without burning time, money, or momentum.
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