Build vs. Buy In-App Chat: The Ultimate Decision Guide

One of the most important product decisions teams face today is whether to build an in-house chat experience or integrate a vendor solution. The following considerations belong at the core of any feasibility analysis, cost approximation, or product roadmap.

In-app chat has quietly revolutionized the way users communicate. Chat is now integral to daily life, building communities, connecting patients with doctors, selling products, solving customers' problems, helping fans rally around their teams, and giving students the tools they need to learn. As consumers, we hardly even notice it. Instead, we notice when chat isn't there.

Consumers may take the ability to send and receive messages for granted, but product teams know that those users' expectations make reliable, scalable chat functionality a critical roadmap item. They know that hundreds of careful architectural decisions back a seamless user experience, and they know that the ability to execute those decisions at the right cost and on the right timeline can make or break a software product's success.

That's where the build vs. buy question comes in.

You have two main ways to add chat to your app:

Build from scratch: Fully customizable, but resource-intensive and complex.
Buy a chat SDK/API: Faster to launch, flexible to customize, and often more cost-effective.

It's worth noting a third option: plug-and-play tools like Tidio or Intercom, with one-size-fits-all UI features and simplified back-end integrations. These solutions are great at solving the exact problems they're intended for, but come up short in terms of customization and adaptability for unique use cases. They're also difficult to embed directly to create a seamless in-app chat experience.

Below, we'll compare the other two in-app chat development options: building chat functionality completely from scratch vs. building on top of a ready-made API or SDK foundation.

With chat becoming a critical feature across:

... The decision to build or buy in-app chat will ultimately depend on your organization's unique requirements.

Still, the baselines set forth here should provide a reliable starting point for any analysis, helping to ensure that universal factors in the decision aren't overlooked.

Evaluate Your App

Before making the decision to build or buy in-app chat, you'll want to zoom out and start with a foundational question:

How closely tied is chat to the core value your product delivers?

In other words, is chat the experience you're selling, or is it a feature that enhances something else? Understanding this distinction will help you determine whether the investment required to build chat from scratch is truly warranted, or whether a modular API/SDK approach would be more aligned with your goals.

Here are key questions to help you assess where chat fits in your product strategy:

1. Is chat a core differentiator or a supporting feature?

Chat is a differentiator if it is the experience. For example, you're building a new messaging platform, real-time collaboration tool, or social product.
Chat is a supporting feature if it enhances your product's core workflows, like connecting customers with support, enabling sellers and buyers to interact, or facilitating team coordination.

If chat is not what sets your product apart in the market, it likely shouldn't require the same level of internal investment as your primary differentiators.

2. Will chat solve internal or external problems?

If the goal is to improve internal workflows (such as agent communication, operations efficiency), chat is non-billable and unlikely to drive direct revenue.
If chat directly supports user-facing experiences (such as boosting retention, driving conversions, enabling core interactions), it's more strategic, but still must be balanced against other roadmap priorities.

Features that don't generate revenue directly, yet consume major engineering time, can slow growth and innovation elsewhere.

3. Would you build other infrastructure tools from scratch?

Few teams today would attempt to build their own email platforms, HR systems, office productivity suites, or project management tools. Even in data infrastructure, where customization used to be the norm, teams have embraced platforms like Snowflake, dbt, and Fivetran to standardize workflows and move faster.

Chat is following this same path. With high-quality, flexible chat platforms already available, investing heavily in building from the ground up often means re-solving a problem already solved.

Weigh the Opportunity Cost

Engineering resources are pricey and finite, often involving hidden costs. They create the most value when focused on your product's core value proposition, not supporting infrastructure. When developers spend months building chat, the true cost isn't just in time or money, but in what they could have built instead.

That lost time often comes at the expense of features that would have improved your product's competitiveness, enhanced user experience, or driven direct revenue. In most cases, those tradeoffs aren't worth it.

"It's kind of tempting, right? If you Google it, you'll find articles like 'Build Your Own Chat In One Week.' But then, you realize these additional use cases like muting users, creating channels, kicking people out of channels, and a million other things—that's when complexity creeps in." — Diego Lopez, CTO at Paired. Read the case study.

Unless you already have a team of experienced real-time messaging engineers, building chat will require a ramp-up period. Developers will need to research existing architectures, test various approaches, and make foundational decisions, none of which produce immediately shippable code.

And as your team gains efficiency and specialization, the cost of diverting them grows. The better your engineers are at delivering high-value features, the more expensive it becomes to task them with building infrastructure outside their expertise.

Even if your use case calls for customization, a flexible API or SDK can deliver a high degree of control with fewer resources. Instead of building from scratch, your team can focus on tailoring the experience and integrating it tightly with your product.

It's also important to remember that building in-house means owning long-term maintenance. After launch, developers will still need to monitor performance, resolve issues, and refactor as your product scales. While this may require fewer hours than the initial build, it remains a recurring cost that pulls focus from roadmap priorities.

Estimate Financial Investment

Total cost is an obvious factor in the build vs. buy decision, but different methods of calculating that cost yield dramatically varied results.

If the internal cost to build chat isn't calculated carefully, for example, unplanned expenses that emerge during development can be so significant that they would have changed the initial decision to build if they had been predicted earlier.

While in-house development often seems like a bigger up-front investment with lower long-term costs, that breakeven point can be misleading. The idea is that recurring SaaS fees eventually surpass the one-time build cost, but in reality, ongoing maintenance and scaling often push that break-even much farther out than expected.

Theoretical Build vs. Buy Cost Over Time

line graph showing build cost vs buy cost over time, with build starting out expensive then tapering and buy showing a consistent low spend

This model may make sense on paper, and for a company with plenty of cash on hand and a desire to plan many years into the future, it may point to building as the right decision.

But for most organizations, the up-front cost of building in-house is significantly higher than a monthly as-a-Service fee, rendering the above model unrealistic.

In many cases, the costs never even out.

After building chat in-house, teams often freeze development to limit costs to hosting and maintenance. But issues like scaling or performance problems can still create unexpected expenses. Many companies also can't afford a long development timeline and need a solution they can launch quickly.

That's why a clear, realistic estimate of in-house costs is essential to making the right build vs. buy decision.

Cost to Develop Chat Functionality In-House

Your own calculation for the time and cost to build chat in-house will depend on variables like developer salaries in your area, the backgrounds and levels of expertise available on your team, and the required use case(s) and feature depth of the chat module. Still, the basic methodology for the calculation should be consistent.

We'll walk through that process and run rough estimates on the low end and the high end: one for building a simple chat feature as fast as possible under perfect conditions, and one for building a highly complex offering with more personnel and some common challenges and roadblocks thrown in.

These build estimates both assume that development is handled by a team of experienced software engineers who work under normal conditions, do not need to balance any other significant projects or priorities, and do not encounter any unplanned setbacks during development.

Here's the most basic version of the equation, with further considerations for each component broken out in more detail below:

Calculating Initial Chat Development Cost

Building a custom in-app chat solution typically requires 3 - 6 months of focused development. Costs can vary widely depending on scope, team size, and location.

→ Low-End Estimate: Basic Live Chat (Intercom-style)

Team: 2 skilled developers
Location: Lower-cost market ($100k/year salary)
Timeline: 2 months
Labor Cost: ~$33,333

Infrastructure Costs (estimated):

AWS services (EC2/Elastic Beanstalk, S3, RDS): ~$1,500/month
Total Infrastructure (2 months): ~$3,000

Total Low-End Build Estimate: $36,333 over 2 months
(Does not include unplanned delays, QA, or iterative changes.)

→ High-End Estimate: Full Collaboration Tool (Slack-style MVP)

Team: 6 developers
Location: San Francisco Bay Area (~$200K/year salary)
Platforms: iOS, Android, Web
Timeline: 5 months
Labor Cost: ~$500,000

Infrastructure Costs (estimated):

Higher resource allocation: ~$4,000/month
Total Infrastructure (5 months): ~$20,000

Total High-End Build Estimate: $520,000 over 5 months
(Conservative estimate, assuming MVP-ready launch.)

These two scenarios show the wide range of upfront investment required. And both still exclude long-term costs like maintenance, scaling, or iterative improvements post-launch.

Calculating Maintenance & Scaling Costs

Now, let's do some similar math to factor in the cost of maintaining, upgrading, and scaling our newly launched in-app chat function based on customer feedback and results over the course of its first year of service.

→ Low-End Maintenance Estimate:

Let's assume things go smoothly:

The original two-person dev team built a horizontally scalable solution on AWS Elastic Beanstalk.
Ongoing maintenance requires two developers for two months/year to handle minor fixes: ~$33,332
Infrastructure usage increases with scale, averaging ~$10,000/month annually. Infrastructure cost for 12 months: ~$120,000

Total year-one maintenance cost: ~$153,332
Running total after 14 months: ~$189,665

→ High-End Maintenance Estimate:

For a more complex, feature-rich chat tool:

Two senior engineers contribute two months each throughout the year: ~$66,667
Strong user adoption drives infrastructure cost to ~$20,000/month. Infrastructure cost for 12 months: ~$240,000

Total year-one maintenance cost: ~$306,667
Running total after 17 months: ~$826,667

After the first year in either scenario, IaaS costs will, of course, recur perpetually, and some degree of maintenance will still be required. All of the costs estimated above can balloon exponentially if, for one reason or another, the first build attempt goes off the rails or doesn't work as planned.

With the above complications in mind, the total cost of in-house development often turns out higher than initially expected.

Its cost also tapers more slowly over time than expected, significantly delaying the date when the total cost to build eventually matches the total cost to buy. It can easily be 5-10 years or longer before the total cost of an in-house build becomes less than the sum of smaller SaaS payments over the same period.

Cost to Buy an In-App Chat Solution

Just like building chat in-house, buying an API-based or ready-made chat solution comes with hidden costs. To evaluate this option accurately, it's important to consider more than just the subscription fee.

One common misconception is that SaaS or API-based solutions have no up-front cost. While implementation is still far less expensive than building from scratch, it's not free. At a minimum, you'll need:

UI customization to match your product's branding
Integration with your app and supporting systems (CRM, analytics, support tools)

Even plug-and-play tools like Tidio, designed for lightweight sales or support chat, still require setup and ongoing tweaks to remain effective.

Compared to plug-and-play options, chat APIs or SDKs offer greater flexibility, but they also require more developer time during implementation. That includes:

Building the bridge between your app and the chat API
Customizing the experience to meet UX and product needs

However, this cost is still significantly lower than a full in-house build. And for teams looking to move fast, many vendors (like Stream) offer UI kits that speed up deployment. Some customers have launched chat features in a live app in under a week using out-of-the-box components.

When evaluating any third-party solution, you should also consider:

Usage-based pricing: High MAUs can trigger overages if not planned for
Add-on features: "Optional" capabilities can become necessary, increasing costs
Ongoing internal labor: Even with vendor-managed infrastructure, your team still needs to monitor and maintain the integration as business needs evolve

Here's a simplified formula to help estimate the total cost of ownership (TCO):

Simplified SaaS total cost of ownership (TCO)

For reference: At 1 million monthly active users, leading chat-as-a-service solutions charge about $15,000/month. That's $720,000 over four years—still less than the nearly ~$900,000 up-front cost of a high-end in-house build.

In-App Chat as a Capital Expenditure vs. an Operational Expenditure

The rise of cloud infrastructure and high-speed internet has fueled the X-as-a-Service revolution, reshaping how companies spend and budget for technology.

What once required large, up-front capital expenditures (CapEx) can now be handled as operational expenditures (OpEx)—lower-risk, recurring costs that are easier to manage. This shift applies directly to in-app chat.

When a choice is available, finance teams tend to prefer OpEx because:

It's easier to forecast and budget.
It avoids the risk of overspending on unexpected issues.
It provides monthly or annual consistency in billing.

With a SaaS solution, the vendor absorbs much of the technical risk. If something breaks or needs scaling, you're not facing surprise development costs. You pay for reliability, often backed by monetary SLAs.

Building your own app? Get early access to our Livestream or Video Calling API and launch in days!

Because enterprise-grade SaaS solutions serve many clients, they:

Distribute development and maintenance costs more efficiently.
Bundle services into single line items that are easier to report.
Offer pricing models that scale with usage and revenue.

This means you get enterprise-grade reliability and support without the overhead of building and maintaining the system yourself.

Capital expenditures, on the other hand, are inherently risky because they require large sums of cash up front without a guaranteed return. If something fails or needs to be reworked, it can trigger emergency spending that wasn't accounted for, throwing off quarterly or annual budgets.

For many teams evaluating the build vs. buy decision, the ability to treat chat as a scalable, predictable OpEx is a significant point in favor of third-party solutions.

Evaluate Speed and Value

In times of economic uncertainty, new tech investments face pressure to deliver fast ROI. As GE's former CIO Gary Reiner put it during the early COVID-19 downturn:

"If it doesn't pay back this year, it's probably not going to get done."

In-app chat has proven value across industries, but speed matters. Projects that launch quickly and generate returns early are easier to greenlight with finance teams and leadership.

Pre-built chat solutions win on this front. While in-house development can take months and require ongoing support, modular APIs or SDKs dramatically reduce time to market.

Based on earlier models, even a highly experienced team will need at least three months to build and launch a basic MVP from scratch.

"Adding video and audio from scratch is extremely hard in my experience. I knew we needed something that would just plug in and work." — James Mtendamema, Founder at Campus Buddy. Read the case study.

Competitive Advantage & Time to Market

Even in stable market conditions, time to market directly affects your competitive edge. Modern CI/CD workflows allow rapid iteration, meaning competitors can ship multiple features while you're still building version one of a chat system.

With an API or SDK, a small team can launch chat in just a few weeks, compared to the 3 - 6 months needed for an in-house build.

Speed also matters for user metrics. In a crowded app ecosystem, app engagement and retention can shift quickly. As users increasingly expect chat by default, delaying its launch, even by a few weeks, can leave your product more vulnerable to competitors in the marketplace.

Select Critical Chat Features

Chat needs vary by use case. A customer support chat may prioritize queuing and ticketing, while a peer-to-peer messaging app might emphasize typing indicators and read receipts. Group chats, meanwhile, often focus on scale and performance.

What's consistent across all use cases is user expectation. Apps like WhatsApp, Slack, Facebook Messenger, and iMessage have set a high bar with features like reactions, link previews, and media support now expected.

And now, the bar has been raised again by AI.

Today's teams expect:

AI-powered onboarding bots (e.g., GPT-based assistants)
Toxicity and content moderation using LLMs
Real-time summarization and contextual insights
Seamless integration with AI providers like OpenAI, Anthropic, and Hive

Building these features in-house is no small task. It requires custom pipelines, prompt tuning, moderation dashboards, and handling rate limits, latency, and edge cases. By contrast, Stream offers built-in support for popular AI providers, enabling teams to deploy advanced capabilities without starting from scratch.

While a basic MVP can launch with just core features, anything less than a modern experience may disappoint users. The more advanced the feature set, the more time and cost are required to build from scratch, whereas top API solutions provide these features out of the box, letting teams focus on what matters most.

Core In-App Chat Features for an MVP Offering

These bare-bones features will need to be developed to support any type of in-app chat or messaging app. Think of them as the project's foundation, upon which further customization may be required.

Keep in mind that the time and cost estimates included in this article were calculated for this type of MVP; additions from the list of advanced features below will require a larger investment.

Even basic functionality can be challenging to implement smoothly. Modern chat apps feel seamless because dedicated teams have refined them over years of development.

Message drafting and editing window with keyboard
Chat window with ability to separate messages by sender and organize messages chronologically
Front-end/UI integration with consumer side of your app
Back-end integration with admin side of your app
Functional commands to send an outbound message, receive, interpret, and display an incoming message, and store messages in an ongoing conversation

Advanced Chat Features to Consider

Depending on your use case and your users' expectations, some of the more advanced features below may actually be considered mission-critical. Others can enhance the overall user experience, helping to drive engagement and retention while giving your brand a competitive polish.

Support for emojis, gifs, in-line images and videos, and file attachments
Threads and replies to keep the main conversation on topic
User-friendly group chats and direct messages
Multi-tenant and team functionality to separate unaffiliated groups of users from each other
Link previews for secure and efficient sharing
Ability to incorporate end-to-end encryption to keep messages secure and out of the hands of advertisers and bad actors
Message search functionality to save users from endless scrolling when they need to find something
Reactions like hearts, laughter, applause, etc.
Capability to connect chatbots via webhooks to conserve human bandwidth in sales and support use cases
Slash commands to help users automate common tasks
Read receipts and typing indicators to keep users engaged between messages
Admin moderation capabilities to prevent inappropriate or unsafe behavior
View a complete list of advanced chat features

Real-World Examples

Many companies have faced the same build vs. buy decision and opted to accelerate growth, reduce complexity, and scale faster by using a ready-made chat solution.

Here's how they made it work:

Rigi: Rapid Integration and 50% YoY Growth

Rigi, a platform that helps creators monetize content, needed a reliable chat experience to support growing communities.

Solution: A single developer integrated Stream's React Native SDK in just a few hours.
Result: Enabled fast time to market and contributed to 50% year-over-year growth.
Impact: Improved community engagement and monetization for creators.

Nextdoor: Cutting Costs While Upgrading Chat

Nextdoor wanted to improve messaging between neighbors and reduce the cost of maintaining its existing in-house chat system.

Switch: Replaced internal solution with Stream Chat.
Savings: Reduced messaging-related costs by 50%.
Value: Delivered richer messaging features while streamlining development.

Hudl: Powering In-App Community for Sports Tech

Hudl aimed to strengthen team communication and build more engaging in-app communities.

Goal: Create a social layer without building from scratch.
Approach: Integrated Stream Chat to enable real-time messaging.
Benefit: Seamless setup and more time to focus on core product innovation.

Identify Risks Involved

All technology and technological investments come with risk, but the amount and type of risk involved in building or buying in-app chat can vary greatly.

Product managers need to assess what level of risk exposure is acceptable and what risks can be minimized or prevented as part of the development or integration process.

Critical areas for review include:

Security and compliance
Data storage
Vendor lock-in
Technical debt
Overall reliability, performance, and scalability

Security & Compliance

Security must be built into your chat infrastructure from day one.

That includes:

Encryption at rest and in transit
MFA/2FA and strong authentication
Least-privilege access for users and infrastructure
Compliance with industry standards like HIPAA, FERPA, PCI DSS, SOC 2 compliance, ISO 27001, and GDPR

Vendor risk: You'll need to trust your provider to maintain these standards. Choose one that treats security as a core practice, not a checkbox.

In-house risk: Securing a custom solution is complex and time-consuming. A vendor focused solely on chat may be better equipped to keep up with evolving threats.

Long-Term Scalability

Underestimating growth is a common mistake. If your system can't handle:

A spike in users
High volumes of messages or channels
Complex concurrency loads

...you may be forced into an expensive, urgent rebuild. And some platforms scale poorly for chat and get costly fast.

Take this tutorial using WebSockets on Cloud Run for example: The author builds chat on auto-scaling infrastructure that can support up to 250,000 concurrent connections, which sounds great. But the compute fees quickly get out of hand, with the author's own infrastructure cost estimate landing at $62,600/month.

A dedicated chat provider, on the other hand, spreads infrastructure and development costs across many client organizations and can afford to invest in the right scalable technology up front. Building chat from scratch with a language like C++, Go, or Scala, for example, may initially be more difficult and costly than building on Cloud Run or Firebase, but pays off as user counts grow. With the right chat API provider, you can rest assured that predictable infrastructure spend and load balancing are taken care of.

"Knowing that Stream supports Enterprises, we are confident that your solution will help us to scale. Stream's global edge network, reliable infrastructure, and SLA uptimes guarantee efficient scalability. As the business expands into larger markets, we are confident that Stream Chat will scale alongside our user base." — Amar Amarsanaa, CEO and Co-Founder at Zaya. Read the case study.

Reliability & Performance

In-house solutions risk:

Laggy performance
Buggy behavior
Uptime issues without 24/7 monitoring

Reliable chat requires continuous testing, optimization, and a response plan. Vendors typically offer SLAs and actively manage uptime, making performance a shared responsibility.

Data & Storage Ownership

Both physical data storage and that data's legal ownership can present complex challenges.

Most leading chat providers, including Stream, rely on trusted cloud platforms like AWS, GCP, or Azure, offering:

Encryption at rest and in transit
Role-based access controls
Compliance with standards like HIPAA, GDPR, and SOC 2

But today, especially with the rise of AI, storage alone isn't enough. How vendors use your data matters just as much.

Stream's privacy stance is clear. We do not mine, sell, or use customer data to train AI models. We're committed to protecting user privacy, especially for regulated industries. This sets Stream apart from some low-cost or freemium providers that may engage in AI-driven data harvesting or monetization.

If you're evaluating a third-party chat vendor, go beyond basic security. Ask: Who owns the data? Is it used for AI training? What privacy guarantees are in place?

Decision Ownership

Internal development will likely give you the most ownership over architectural decisions, new feature priorities, and custom integrations.

The downside to this is that each decision takes time to research and approve, and may be influenced by incomplete or unproven data. A vendor's API or SDK solution will likely have been tested and proven across a wide variety of use cases, so you can trust that major functional decisions have been carefully made and focus instead on creating the best experience for your users.

Technical Debt

Internal teams often cut corners to stay on schedule, leading to:

Known issues that degrade UX
Long-term architectural limitations
Costly refactors down the road

These decisions can degrade the user experience during critical growth phases and may be costly, or impossible, to fix later.

Buying a chat solution shifts that maintenance burden to the vendor. While you won't own the product roadmap, the right partner will keep you informed and responsive to evolving needs.

Stream addresses this concern head-on by actively shipping improvements and fixes, publishing a transparent weekly changelog, and listening to customer feedback to inform feature priorities.

Cross-Platform Development

Chat will likely need to function similarly across iOS, Android, web, and possibly desktop native platforms. Each platform presents its own unique challenges and requires a different developer skill set.

Organizations that choose to build chat will need to invest equally in development across each of these platforms or risk delivering a disappointing and inconsistent experience on one or two of them, inviting negative user reviews.

Vendor Lock-In

Vendor lock-in is a real concern, especially with multi-year contracts, shifting priorities, or platform changes outside your control. But what's often overlooked is that building in-house can lead to even tighter lock-in, especially if:

The architecture doesn't scale or adapt
Institutional knowledge is lost when developers leave
Documentation isn't maintained for future teams

The good news is that not all vendors lock you in. At Stream, we design with portability and long-term flexibility in mind.

This means we support data export and provide tools to make migration easy. Our APIs and SDKs are structured to minimize coupling, making it possible to transition smoothly if needed. And we believe data belongs to you, not us.

The takeaway on vendor lock-in, then, is that no solution should be treated as entirely permanent. If you choose to build chat in house, make sure your code is well documented and the overall architecture will make sense to any skilled engineer outside of the original dev team. If you choose to buy an in-app chat solution, make sure you trust the vendor's financial footing and market stability and confirm its product is modular enough that migrating away from it in the future would not cause a catastrophic failure for your own product.

Make the Final Build vs. Buy Decision

The decision to build or buy chat functionality can't be made lightly. It plays a direct role in your product's ability to delight users and solve their problems, driving engagement and retention.

The decision also has significant financial implications, with an impact on budgeting and prioritization of engineering resources. It's a decision that must be made with your organization's unique value proposition, customer base, goals, and requirements in mind.

Paired with these factors, the analysis above should help to produce an exhaustive list of pros and cons of building or buying in-app chat functionality, supporting a carefully informed decision.

For many organizations, the advantages gained in up-front cost, total cost, time to market, and feature depth will make a chat API or SDK solution the logical choice. Still, for others with enough cash and development resources available or with a completely revolutionary vision for how chat looks and functions, in-house development may be worth the investment.

If you and your team are still compiling your evaluation and could use some input from a technical expert in chat development, please don't hesitate to contact us.