Tech
Microservices in BPM – Embracing Composable Automation
Organizations in every sector look to Business Process Management (BPM) for ways to streamline everyday tasks, respond faster to changing conditions, and reduce the fatigue of manually tracking paperwork. However, traditional BPM systems often bundle every feature into a single, expansive platform. That approach can make it complicated to adapt or scale individual functions—such as invoice approvals or HR onboarding—without updating the entire application. As companies grapple with rapidly shifting workflows, many turn to microservices architectures that align with Gartner’s prediction: most enterprises will choose “composable” technology models, where each business capability is activated on demand and integrated seamlessly.
Microservices break large applications into smaller, standalone components that run independently, yet coordinate through clear communication channels. In a BPM context, that means each phase of a process—document classification, AI-driven data extraction, user approvals—can be managed by its own specialized service. This modular approach helps teams roll out new features quickly, fix issues with minimal system-wide disturbance, and scale only the parts of the application that face heavier load. Whether processing a batch of sales orders, handling a surge of support tickets, or introducing new AI tools, composable BPM accommodates those needs without forcing major overhauls.
Monolithic BPM vs. Composable Architecture
A traditional BPM monolith tries to address every automation requirement under one roof. From building process models and setting permissions to storing documents and generating analytics, everything relies on the same codebase. While it may work well for stable, predictable environments, this all-or-nothing model can become a bottleneck in fast-moving scenarios. Even a minor software patch might require lengthy testing across every module.
Microservices-based BPM takes the opposite tack: each function or module operates as its own service. An orchestrator might oversee how tasks flow, but individual components—like a rules engine or an AI recognition step—are developed, deployed, and scaled independently. Teams maintain agility, because adding or updating a service no longer entails comprehensive system testing. If a new invoice-matching algorithm proves beneficial, it can be deployed alongside the existing system without rewriting everything else.
Why It Matters for Flexible Process Automation
A composable BPM solution that uses microservices delivers significant advantages for operational teams and IT planners alike. Process owners can mix and match capabilities more freely, introducing features like advanced analytics or AI-based classification only when needed. A seasonal HR spike, for instance, can prompt teams to temporarily ramp up the microservice that digitizes and categorizes onboarding documents. Once the hiring wave passes, resources shift elsewhere—avoiding unnecessary licensing or infrastructure expenses.
Gartner’s view of a flexible, composable future underscores how microservices address the ebb and flow of real-world demand. Rather than investing in broad-scale platform expansions, organizations implement targeted enhancements in the precise areas that matter. Updates happen rapidly, as each microservice adheres to standard interfaces—new developments are integrated just by pointing the orchestrator to the correct endpoints. That capacity for continuous evolution aligns well with a corporate landscape where regulations, market conditions, and customer preferences evolve at a rapid pace.
Tighter AI Integration
Business processes increasingly rely on AI: from automated text extraction in finance to predictive analytics in supply chain. Microservices make it easier to embed these capabilities. Instead of implementing AI features in the entire BPM suite, an AI microservice focuses on the relevant tasks. A finance department might configure a microservice that reads invoices, extracts totals or line items, and confirms matching purchase orders. If newer AI libraries or techniques improve accuracy, developers swap in the upgraded model, leaving other parts of the process unchanged.
Companies can also deploy multiple AI-based microservices if needed—such as one for language translation and another for advanced fraud detection—without concern that these expansions will clash within a monolithic framework. The orchestrator merely routes each workflow to the right microservice at the right time. Implementation becomes simpler, ensuring staff can quickly see how new AI tools enhance routine steps.
On-Demand Scalability
Not every facet of BPM demands equal capacity at all times. One microservice might handle a trickle of small tasks, while another faces periodic spikes. Monolithic BPM typically forces teams to scale everything together, which can be costly in both infrastructure and licensing. Microservices allow distinct scale policies for each component. If a customer service workflow experiences surging ticket volume, only the associated microservice is replicated. Meanwhile, document archival or reporting services can remain at minimal capacity until needed.
Composable operations further reduce overhead by letting organizations introduce new processes or services based on actual data about usage. If an HR department seldom uses a specialized feature, it no longer sits dormant in a large suite. In the microservices model, seldom-used modules can be turned off or only activated during relevant periods. That targeted approach aligns with the broader shift toward usage-based billing, an evolving practice that resonates with many CFOs.
Low-Code Tools in a Composable World
Modern BPM platforms often include low-code or no-code development interfaces that let non-technical staff configure workflows. When BPM is microservices-based, these user-friendly interfaces can orchestrate multiple discrete services behind the scenes. An HR manager, for example, might design a step to request background checks, call an AI microservice to read the results, then route a final decision form to a senior manager. Despite the complexity of calling separate services, the low-code environment presents a single cohesive flowchart.
That means employees can adapt processes, add new conditions, and refine tasks without writing extensive code. The composable nature of the underlying architecture ensures that if a specific microservice for e-signatures is replaced, the BPM design only updates that reference. The rest of the process remains intact.
Concrete Examples of Microservices-Based BPM
Imagine a retail operation automating its online order fulfillment. The composable BPM orchestrator triggers individual microservices: a payment validation service, an inventory checker, a shipping label generator, and a notification sender. If the retailer decides to adopt a new shipping provider, developers update the shipping microservice or add another. The rest of the flow stays untouched, and customers see no disruption.
Another case is a manufacturer’s supply chain that includes inbound QA checks for raw materials. With microservices, each QA station can run a specific module that measures or inspects certain attributes, pushing data back to the BPM orchestrator. If a new standard arises—maybe a more rigorous test for product safety—engineers adapt only the relevant QA microservice. The microservices approach also helps track the status of every container or shipment in real time.
A Glimpse into the Future of Automation
Analysts emphasize that composable technology is not a passing trend but the foundation of next-generation IT. As new data streams—like Internet of Things sensors or AI-based intelligence—become available, microservices-based BPM can incorporate these quickly. Each addition is simply another service that interacts with the existing orchestration logic. That architecture encourages experimentation: if an innovative approach works, it scales; if not, it can be easily removed.
One example of this shift is Sys.tm Flows, a tool that highlights how a microservices framework can pair BPM functionality with AI-based enhancements and flexible pricing. By letting organizations activate and pay for only the services they need, Sys.tm Flows illustrates the larger point: the future belongs to individually deployable building blocks that combine into powerful automation.
For process owners and CIOs seeking real agility, the microservices approach solves persistent issues with monolithic BPM, fosters continuous updates, and provides refined control over capacity. It also offers a consistent environment to integrate emerging AI capabilities and evolving compliance mandates, all without imposing sweeping upgrades on the entire solution.
Moving Forward
Microservices in BPM embody the principles of composable automation: creating a dynamic, building-block style system that can pivot quickly. Instead of waiting for a single, sprawling suite to evolve, each service operates independently and scales to match moment-by-moment requirements. This model harmonizes with Gartner’s predictions that more organizations will shift to composable architectures to stay competitive, handle fluctuating demand, and incorporate fast-moving innovations. By treating each part of a workflow as its own microservice, businesses gain the freedom to upgrade, experiment, and adapt with minimal impact on other processes. For many, it represents the next logical step in transforming BPM from static blueprint to an agile, ever-improving engine of productivity.
In the evolving world of digital marketing, staying active on social media has become crucial for brands, influencers, and businesses alike. But managing daily posts, engaging with followers, and keeping up with trends can take up a lot of time and energy. That’s where social media automation comes in—a powerful solution to simplify and streamline your online marketing efforts.
With automation tools, you can schedule posts, monitor engagement, and even interact with your audience without having to be online 24/7. For platforms like Instagram, which require frequent interaction to maintain visibility, using a nice Instagram bot can make a noticeable difference. These bots help automate actions such as following, liking, and commenting, enabling you to grow your account organically and consistently.
If you’re aiming to build a strong Instagram presence in 2025, a nice Instagram bot can be an essential part of your strategy. Instead of spending hours managing tasks manually, automation lets you focus on what truly matters—creating high-quality content and connecting meaningfully with your audience.
What Is Social Media Automation?
Social media automation refers to the use of tools and software to handle routine tasks on social platforms. These tasks can include:
- Scheduling and publishing posts
- Auto-replying to comments or messages
- Following and unfollowing accounts
- Liking and engaging with posts
- Tracking performance metrics
These tools are designed to help users maintain a consistent online presence while saving time and effort. Automation is not about removing the human element—it’s about making your workflow more efficient.
5 Key Benefits of Social Media Automation
- Time-Saving Efficiency – Automate repetitive tasks and focus more on creative content.
- Consistent Posting Schedule – Never miss an ideal time slot with pre-scheduled content.
- Better Engagement – Use automation to like, comment, or follow users based on filters.
- Analytics & Reporting – Track post performance and user engagement with built-in dashboards.
- Scalable Growth – Tools like a nice Instagram bot help scale your Instagram presence without manual work.
How to Automate Social Media Safely
To get the best results, it’s important to use automation smartly. Here are some tips:
- Choose trusted tools that follow platform policies.
- Avoid spammy tactics like mass-following or repetitive commenting.
- Combine automation with manual interaction to stay authentic.
- Monitor your results and tweak your strategy regularly.
- Focus on quality content while automation handles the routine.
Why Instagram Automation Is Trending in 2025
Instagram remains one of the most dynamic platforms for brand growth and user engagement. But standing out in a crowded feed requires both consistency and smart strategy. That’s why many marketers now rely on automation tools—especially a nice Instagram bot—to get ahead of competitors.
These bots are designed to interact with your target audience, helping you build a real following and boost engagement, all without violating Instagram’s terms of service. When used responsibly, they can be your silent growth partner.
Conclusion
Social media automation isn’t just a convenience—it’s a smart strategy for digital growth. Whether you’re a solo content creator or managing multiple brand accounts, the right tools can help you save time, improve consistency, and scale effectively. By integrating a nice Instagram bot into your routine, you can boost your reach while focusing on building real, valuable connections with your audience.
Embedded analytics means integrating dashboards, reports, and visualizations directly into your software product. Instead of switching to external BI tools or exporting data into spreadsheets, users get insights in context right where decisions are made.
For SaaS companies, embedded analytics has moved from a “nice-to-have” to a core product capability. It enhances user experience, drives retention, unlocks monetization opportunities, and alleviates the load on your development team. However, not all embedded analytics platforms are built the same, and the wrong choice can result in bloated integrations, confusing pricing, or poor adoption.
This list focuses on the top five embedded analytics platforms in 2025 based on developer flexibility, product fit, scalability, and real-world value. Whether you’re evaluating your first analytics vendor or replacing legacy BI, these are the tools worth looking at.
Reveal Overview
Reveal is a developer-focused embedded analytics platform designed specifically for SaaS and ISV products. Unlike traditional BI tools that offer limited embedding through iFrames, Reveal provides native SDKs that integrate directly into your application’s codebase. This approach gives teams complete control over the user experience, branding, and dashboard behavior—making analytics feel like a seamless part of the product, not an external add-on.
Reveal is also one of the few platforms with flat, transparent pricing. It avoids the per-user, per-report, or data-volume-based fees common to legacy BI tools. That makes it easier to forecast costs and scale analytics alongside your product without penalty.
Strengths
- Native SDKs (not iFrames): Available for .NET, JavaScript, React, Angular, and more—delivers real integration and interactivity
- Full white-labeling: Customize logos, colors, layouts, and interactions to fully match your product’s UI
- Flat pricing: One predictable fee, no matter how many users or dashboards you support
- Self-service dashboard creation: Non-technical users can build and edit dashboards without relying on dev resources
- Flexible deployment: Supports cloud, on-prem, or hybrid models depending on infrastructure and compliance needs
Best For
SaaS product teams and ISVs that want fast time-to-market, complete UI control, and cost predictability. Ideal for teams embedding analytics into customer-facing apps where seamless UX and real-time data access matter.
Limitations
Reveal isn’t a general-purpose BI platform. It’s optimized for product embedding, not for internal business intelligence or standalone reporting dashboards across departments.
GoodData
GoodData is a composable analytics platform built for complex, multi-tenant environments. It’s geared toward developers and enterprise data teams who need complete control over how analytics are delivered, secured, and customized. Its headless architecture allows teams to build fully custom front ends, using a GraphQL API to query and present data however they choose.
GoodData is especially strong in data governance and scalability. It supports large-scale deployments with strict data control requirements, and integrates with modern data stacks without forcing a single rigid workflow.
Strengths
- Headless, API-first architecture: Use GraphQL to deliver analytics via custom front ends or existing UI frameworks
- Built for multi-tenancy: Designed to support embedded analytics across many customers or departments, with strict data isolation
- Enterprise-grade governance: Fine-grained access controls, versioning, and audit trails built for compliance-heavy use cases
- Flexible deployment: Can be run in the cloud or self-hosted, with strong Kubernetes support for complex environments
- Scales with your data: Optimized for distributed, high-volume data environments
Best For
Enterprises or platform teams managing complex data pipelines across multiple tenants. Ideal for those who need to control every layer of the analytics stack—from data modeling to UI delivery.
Limitations
The architecture assumes strong engineering resources. For teams unfamiliar with headless BI or GraphQL, the setup and customization process can require a steep ramp-up.
Looker (by Google Cloud)
Overview
Looker is a well-established enterprise BI platform known for its semantic modeling layer, LookML, and deep integration with the Google Cloud ecosystem. While not designed specifically for embedding, it offers APIs that allow teams to surface analytics in external applications with some customization.
Looker’s main appeal lies in its centralized data governance and reusable data models. For teams that prioritize consistency across reports and dashboards, especially within large data teams or cross-functional environments, Looker provides structure and scale.
Strengths
- LookML modeling layer: Enables centralized, reusable definitions of metrics, dimensions, and logic
- Robust API access: REST and SDK-based APIs allow programmatic dashboard delivery and data queries
- Native to Google Cloud: Integrates tightly with BigQuery and other GCP services for fast performance and scalability
- Strong governance: Version control, permissions, and approval workflows support enterprise needs
- Interactive dashboards: Supports filtering, drill-downs, and custom visualizations
Best For
Enterprise organizations already using Google Cloud that want governed, reusable analytics models across multiple teams and use cases.
Limitations
Looker is not SDK-based, and embedding is done through iframes or API workarounds. Customization and white-labeling are limited compared to platforms built specifically for embedding inside SaaS products.
Sisense – Overview
Sisense is an embedded analytics platform focused on extensibility and developer control. It provides a flexible architecture that lets engineering teams tailor analytics to fit a wide range of product and user requirements. Sisense supports embedding via JavaScript libraries, REST APIs, and web components, allowing for custom UI integration and interactive dashboards within web applications.
Its back-end architecture can handle large, complex data pipelines, making it suitable for enterprise-grade use cases. Sisense also supports a wide range of deployment models, including cloud, hybrid, and on-prem, which is valuable for teams with specific compliance or infrastructure needs.
Strengths
- Extensive API toolkit and plugin framework: Customize functionality, visualizations, and workflows
- Flexible embedding methods: Use JavaScript, REST APIs, or web components depending on stack
- Scales with complexity: Handles high-volume data environments and multi-source pipelines
- Deployment flexibility: Supports cloud, hybrid, and on-prem use cases for compliance-driven teams
- Developer-friendly: Built for teams with engineering resources to create custom analytics experiences
Best For
Engineering-led teams that need advanced customization across diverse products, use cases, or customer segments.
Limitations
Sisense pricing is usage-based and can become expensive at scale. Teams embedding into fast-growing SaaS products may need to plan carefully for long-term cost and licensing structures.
Logi Analytics (by Insightsoftware) – Overview
Logi Analytics is a long-standing player in the embedded analytics space, known for its deep integration capabilities—especially in .NET and legacy environments. It’s designed for teams that want to add analytics to existing apps without rebuilding their tech stack. Logi supports strong white-labeling and flexible customization, making it a practical fit for internal tools or customer-facing apps that need retrofitted analytics.
Strengths
- Optimized for legacy stacks: Embeds cleanly into .NET and older enterprise systems
- White-label and brand customization: Adapt analytics to match your existing UI
- Custom workflow support: Tailor interactivity and logic based on user roles or actions
- Flexible user model: Works for both internal teams and external customers
Best For
Organizations modernizing older applications that need to integrate analytics without rewriting their front end or moving off legacy infrastructure.
Limitations
Since being acquired by Insightsoftware, innovation has slowed. Some users report performance issues when dealing with complex views or large-scale deployments.
Choosing the Right Embedded Analytics Platform
The best embedded analytics platform isn’t the one with the most features—it’s the one that fits your product. You need something that integrates directly into your app, matches your UI, performs in real time, and scales without surprise costs or added dev work.
If you’re embedding analytics into a customer-facing product, prioritize:
- SDK-based integration (not iFrames)
- Full control over branding and layout
- Real-time data performance
- Transparent, predictable pricing
Whether you’re launching analytics for the first time or replacing a rigid BI tool, these five platforms are the top options to consider in 2025.
Marketplaces need payment systems that do more than just process transactions. You’re not just selling one product—you’re connecting buyers and multiple sellers. That means more complexity, more compliance, and a bigger need for flexibility. So, what’s the best payment gateway for marketplace businesses?
In this guide, we break down the features to look for, the common pain points, and how to evaluate different options based on your needs.
What Is a Marketplace Payment Gateway?
A payment gateway for a marketplace is a bit more difficult that a standard e-commerce gateway. The nuance is that marketplace payment systems must let multiple vendors accept payments through a single checkout. It also must split those payments—automatically or manually—and it must have an efficient payout feature to ensure each party gets their fair share.
But the best payment gateway for marketplace operations should do more than process payments. It should help you:
- Stay compliant with financial regulations
- Manage payouts to sellers
- Handle refunds and disputes
- Track and report transactions across vendors
Key Features of the Best Payment Gateway for Marketplaces
Multi-Vendor Support
Running a marketplace means handling a wide range of sellers—sole traders, SMEs, and sometimes even large brands. Your payment system needs to support flexible, scalable onboarding that works for all of them.
This includes thorough KYC (Know Your Customer) or KYB (Know Your Business) checks, generating unique account IDs for accurate tracking, and handling region-specific tax requirements. Ideally, much of this should be automated to reduce friction for both you and your sellers while staying compliant.
Split Payments
Splitting a single payment between multiple recipients is not just a nice-to-have—it’s essential for marketplace operations. Whether you’re taking a fixed commission, a dynamic cut, or distributing funds to additional service providers (like delivery partners or charities), your payment gateway should support this natively.
Look for tools that let you configure flexible payout logic—either predefined or based on transaction data. Manual workarounds or after-the-fact calculations won’t scale and open the door to errors or trust issues.
Fast Payouts
Timely payouts build trust. Sellers—especially individuals or gig workers—expect to receive their earnings quickly and predictably. Your payment gateway should offer options for daily, weekly, or on-demand settlement, ideally with support for instant payouts where available.
Transparent payout timelines and status tracking can help reduce support queries and increase seller satisfaction, which in turn benefits the overall health of your platform.
Flexible Payment Methods
A diverse buyer base comes with a wide range of preferences, especially in international markets. Your checkout should support a mix of payment methods to meet users where they are. This includes cards, bank transfers, digital wallets, and local payment methods popular in specific regions. Increasingly, pay-by-bank (A2A) options are gaining traction for their speed and low cost.
Offering multiple payment rails improves conversion and signals reliability across different customer segments.
No-Code or Low-Code Tools
Not every marketplace has a large dev team. In that case, access to ready-made, flexible integration options becomes crucial. Look for payment providers that offer no-code or low-code tools such as hosted checkouts, plug-and-play SDKs, or embeddable payment links.
These allow you to get up and running quickly, reduce development overhead, and still provide a smooth user experience—especially helpful for newer platforms or side projects.
Onboarding and Compliance Tools
Regulatory compliance can be complex and time-consuming, particularly when onboarding vendors across multiple jurisdictions. The right payment gateway will handle much of this behind the scenes—automating anti-money laundering (AML) checks, flagging suspicious activity, and keeping accurate records for audit purposes.
Bonus points for dashboards that help you monitor onboarding progress, generate compliance reports, and reduce manual intervention.
Dispute Management
Disputes in marketplaces are more complicated than in single-merchant models, since both the buyer and seller have a stake in the outcome.
Look for payment systems that offer marketplace-specific features: the ability to issue refunds from seller balances, share chargeback liability based on predefined rules, and manage disputes through a dedicated dashboard. Clear, transparent processes protect everyone involved and prevent minor issues from escalating.
Benefits of Choosing the Right Gateway
- Lower Operational Costs: Manual tasks like reconciliation, KYC checks, and payout tracking can drain time and resources. A smart, automated payment system lightens the load and cuts costs.
- Better Vendor Retention: Reliable, timely payouts build trust. When sellers know they’ll be paid on time and can access clear reports, they’re more likely to stay and grow with your platform.
- Improved Customer Experience: A seamless checkout process—especially one that supports local methods and mobile-first design—leads to higher conversion rates and fewer abandoned carts.
- Scalability: The right gateway grows with you. Whether you’re onboarding 10 vendors or 10,000, it should support increasing complexity without requiring constant manual oversight.
Evaluating the Best Payment Gateway for Marketplace
Here’s what to check when choosing a provider:
| Feature | Why It Matters |
| Multi-currency support | For international buyers and sellers |
| Local payment methods | For better regional conversion |
| Instant payout options | Improves vendor loyalty |
| Automated tax tools | Saves time and ensures compliance |
| API + dashboard access | Combines flexibility with ease-of-use |
| Open banking integrations | Reduces fees, supports pay-by-bank flows |
| Support and SLAs | Essential if something breaks |
Why Pay-by-Bank Matters for Marketplaces
Pay-by-bank is an innovative payment method that’s rapidly gaining ground—particularly in Europe. For marketplaces, it offers a compelling combination of lower fees, faster settlement, and stronger security compared to traditional card payments.
One of its biggest advantages is the potential for instant payments and payouts, which is especially valuable in multi-vendor environments. This payment method became viable with the introduction of open banking, which allows businesses to process direct bank-to-bank transactions within their websites or apps—completely bypassing card networks.
Open banking was introduced in Europe in 2018 under the PSD2 regulation. It required major banks to open up secure APIs to licensed third parties, enabling access to payment infrastructure and customer data (with consent). This regulatory shift unlocked a wave of fintech innovation, making efficient, low-friction payment methods like pay-by-bank possible at scale.
Getting Started with a Marketplace Payment Gateway
You don’t need to overhaul your entire platform to begin offering pay-by-bank. Many modern payment providers are designed with flexibility in mind, making integration smoother than you might expect. Look for options such as:
- Hosted checkouts that handle the payment flow for you, with minimal setup
- Plug-and-play integrations for popular platforms and marketplaces
- Clear API documentation for more custom setups
- Sandbox environments so you can test everything before going live
Start with a limited rollout—perhaps a single product line or a few vendors—to see how the system performs. As you gain confidence, you can expand gradually, reducing risk while scaling effectively.
Final Thoughts
The best payment gateway for marketplace businesses isn’t just about processing payments. It’s about supporting your ecosystem—buyers, sellers, and your team.
Look for something flexible, secure, and scalable. Make sure it handles split payments well, supports pay-by-bank, and fits your region’s legal and banking frameworks.
If you want fewer support tickets, happier sellers, and smoother checkouts—your payment gateway choice will make all the difference.
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