How Solana Uses Inkeep to Scale Developer Support Without Expanding Their Team

TL;DR

The Solana Foundation is a non‑profit tasked with securing, decentralizing, and promoting the adoption of the Solana blockchain.

• Challenge: Solana Foundation faced exponential growth in developer documentation and support needs as their ecosystem expanded, outpacing traditional support capabilities
• Decision: Build vs. buy analysis revealed significant complexity and unpredictable costs in creating in-house RAG infrastructure, observability, and data pipelines
• Solution: Inkeep delivered immediate ROI through AI Chat, Unified Search, and MCP analytics with SOC 2 compliance and predictable pricing
• Results: Drastically reduced time-to-answer for developers, extended support capacity without hiring, and improved documentation discoverability by 10x
• Key Differentiator: Trust-based approach with high answer reliability, enterprise-grade security, and technical team capability that matched Solana's needs

Problem: Scaling Support to Fast Growing Community

The Solana Foundation faced a challenge familiar to any rapidly scaling technology platform: their developer ecosystem was growing exponentially, but their support infrastructure wasn't keeping pace.

As one of the fastest-growing blockchain platforms, Solana's documentation volume expanded dramatically with each new product release, SDK update, and ecosystem integration.

"Giving users an easier way to discover the right content and shorten their learning curve was a clear need, especially as our ecosystem grew and the volume of product information expanded" – John Liu, Solana Developer Relations.

The team initially considered building an in-house AI solution to surface information more effectively to their developer community. However, the technical requirements quickly revealed the true scope of this undertaking:

• Backend Infrastructure Complexity: Building a production-grade RAG (Retrieval-Augmented Generation) service required dedicated engineering resources that would be diverted from core product development. The infrastructure alone, from vector databases, embedding pipelines, and model serving, represented months of engineering work.
• Documentation Gap Analysis: Without visibility into what developers were searching for but not finding, the team couldn't identify critical gaps in their documentation. This blind spot meant potentially thousands of developers struggling silently with undocumented features or unclear explanations.
• Crypto-Specific Requirements: The blockchain community demands unique observability and guardrails. Scam prevention, accurate technical responses about consensus mechanisms, and protection against malicious prompt injection all required specialized expertise that general AI solutions couldn't provide.
• Data Pipeline Management: Solana's documentation lived across multiple repositories, wikis, and third-party integrations. Building and maintaining ingestion pipelines to keep AI responses current would require ongoing engineering investment.
• Unpredictable Costs: LLM inference costs, benchmark testing, error handling, and fallback systems created budget uncertainty. Without clear pricing models, the total cost of ownership for an in-house solution could spiral unexpectedly.

Solution: Platform that Combined Comprehensive Features with Technical Capability & Trust

The Solana Foundation discovered Inkeep through Fumadocs, the open-source documentation framework they were already using. As a sponsor of Fumadocs, Inkeep had already demonstrated commitment to the open-source developer documentation ecosystem—a signal that resonated with Solana's team.

"Many platforms had approached us, but Inkeep stood out with the right mix of trust-based approach, platform features, and technical capability of its people," noted John Liu.

"Inkeep solved all this with one platform and a predictable pricing model."

What differentiated Inkeep from other vendors wasn't just features. But rather it was the comprehensive platform approach that addressed every pain point:

• Trust and Security First: Inkeep's SOC 2 Type compliance provided the enterprise-grade security assurances necessary for a platform handling millions of developer queries. The high reliability of answers meant Solana could confidently deploy AI assistance without constant supervision.
• Integrated Feature Set:
  • AI Chat provided contextual, accurate responses directly from Solana's curated documentation sources
  • Unified Search upgraded their existing search functionality, surfacing resources beyond core documentation
  • Model Context Protocol (MCP) enabled sophisticated analytics and conversation tracking
  • High customizability allowed tailoring to Solana's specific technical requirements and branding through Inkeep's UI Kit.
• Technical Excellence: The Inkeep team's deep understanding of both AI/ML infrastructure and developer documentation needs meant Solana wasn't just buying software—they were gaining a technical partner who understood their challenges intimately. For example, Nick Gomez, Inkeep's CEO & Founder, previously wrote developer docs at Microsoft.

Implementation

The implementation process validated Solana's buy decision. What would have taken months to build internally was operational within weeks:

Week 1-2: Integration and Configuration

• Seamless integration with existing Fumadocs framework required minimal code changes
• Source curation to ensure AI training on authoritative documentation only
• Initial configuration of response parameters and tone

Week 3-4: Customization, Analytics & Optimization

• Crypto-specific guardrails implementation
• Custom prompt engineering for Solana's technical terminology
• Beta testing with internal developer relations team
• MCP analytics setup for tracking engagement metrics
• Feedback loop configuration for continuous improvement
• Performance benchmarking against baseline support metrics

Results

The impact was immediate and measurable across multiple dimensions:

• Support capacity expansion via increased answers to questions
• Documentation gap discovery via Inkeep's Gap Reports
• Cost efficiency via headcount reduction

For support of Capacity Multiplication, Inkeep "enabled Solana to deliver reliable, scalable developer support without needing to significantly expand the team," reported John Liu.

"It effectively extends our capacity, allowing us to assist users at scale in ways that wouldn't have been possible otherwise."

Documentation Discovery: The Unified Search feature surfaced previously hard-to-find resources, reducing documentation redundancy and improving overall content utilization.

Cost Efficiency: By handling the large share of support needs directly through AI, Inkeep delivered measurable ROI:

• Avoided hiring additional developer relations engineers
• Reduced documentation maintenance overhead
• Predictable monthly costs versus variable LLM inference charges

Developer Experience Enhancement: Developers reported finding answers faster, understanding concepts more clearly, and successfully implementing Solana features with less friction—directly impacting ecosystem growth metrics.

Expanded Adoption

The MCP analytics capability has become central to Solana's developer experience strategy, providing unprecedented visibility into developer needs:

Conversation Intelligence:

• Pattern recognition across thousands of queries identifies emerging documentation needs
• Topic clustering reveals which concepts require additional explanation
• Query failure analysis drives documentation improvements

Continuous Improvement Loop:

• User feedback (thumbs up/down) directly influences response quality
• Saved conversations create a knowledge base for edge cases

Performance Monitoring:

• Real-time tracking of response accuracy and relevance
• Latency monitoring ensures consistent user experience
• Error rate tracking with automatic escalation for critical issues

This data-driven approach has transformed how Solana prioritizes documentation updates and identifies gaps in developer resources.

Key Takeaways for Teams

For enterprise leaders evaluating AI-powered documentation solutions, Solana's experience offers critical insights:

1. Build vs. Buy Economics Are Clear: The total cost of building and maintaining an in-house RAG solution far exceeds licensing a purpose-built platform. Engineering time, infrastructure costs, and ongoing maintenance create hidden expenses that compound over time.
2. Security Cannot Be Compromised: SOC 2 compliance and enterprise-grade security are table stakes for any solution handling developer queries. Inkeep's security posture met Solana's stringent requirements without additional configuration.
3. Platform Approach Delivers Superior ROI: Point solutions create integration challenges and data silos. Inkeep's integrated platform—combining chat, search, and analytics—delivered value across multiple touchpoints.
4. Vendor Technical Capability Matters: The complexity of AI implementation means vendor expertise directly impacts success. Inkeep's team understood both the technical challenges and the developer experience requirements.
5. Predictable Pricing Enables Planning: Variable LLM costs make budgeting impossible. Inkeep's predictable pricing model allowed Solana to confidently scale their implementation.

Looking Forward

Solana's success with Inkeep helped the Foundation set a new standard for developer experience in the crypto ecosystem. The Foundation plans to expand their Inkeep MCP implementation, leveraging the protocol's capabilities to create even more sophisticated developer assistance tools.

"Inkeep has improved discoverability, reduced friction for new users, and helped us deliver a better user experience for our docs" – John Liu, Solana Developer Relations.

"As we expand our MCP implementation, we expect to unlock even more value through deeper integration with our development tools and more sophisticated conversation intelligence."

For enterprises facing similar documentation and support scaling challenges, Solana's implementation demonstrates that AI-powered agents can fundamentally transforms how organizations serve large developer communities.

The combination of immediate ROI, predictable costs, and continuous improvement through analytics makes platforms like Inkeep essential infrastructure for any organization serious about developer experience.