We build advanced AI systems that other teams can't deliver
Meet Softcery: We're the AI engineering team that B2B SaaS founders call when other teams say "it's impossible" or "it'll take 6+ months." We specialize in building AI that actually works in production, handles real customer complexity, and scales with your product.
You're here because something isn't working.
Prototype → production gap?
Your prototype proves the concept, but you need professional execution to create a market-ready system.
Launch feels too risky?
You built something functional, but launching means risking data leaks, crashes, or critical issues you can't fix.
Random AI breakdowns?
Your AI fails unpredictably, and you can't figure out how to make it work reliably every time.
Customer customization chaos?
You're saying yes to every early customer request, but now you're building everything for everybody.
Basic AI hit its limits?
Your simple integration kind of worked, but customers want sophisticated features your system can't deliver.
Need impossible AI features?
Your product requires genuinely difficult AI functionality, and you need someone to figure it out.
We've shipped 20+ AI systems for B2B SaaS founders across legal tech, marketing automation, e-commerce, and CRMs. These problems aren't new to us.
Here's how we solve these problems:
Understanding the problem space before writing code
We map edge cases and build test datasets from real production scenarios, not clean synthetic data that breaks in production.
Architecture informed by 20+ production AI launches
We make architecture decisions based on 20+ production launches across legal tech, marketing automation, e-commerce, and CRM.
Early production deployment and beta testing
We deploy to production in the first weeks and launch to 5-10% of users to learn what actually breaks.
Real-time quality evaluation on every response
We validate every response against quality criteria and flag failures immediately before they reach customers.
Observability that surfaces problems before customers do
We implement request IDs, execution tracing, and structured logging so failures can be reproduced and debugged.
Automated end-to-end testing infrastructure
We build automated test suites that catch breaks on every code change instead of weeks later from customer complaints.
Most teams skip these steps and ship broken AI. We've built the systems to get it right the first time. Get the AI Launch Plan or schedule a consultation to learn more.
Complete AI engineering capabilities.
Conversational AI
Text Agents
Chat-based AI agents with context, memory, and tool integration.
Voice Agents
Real-time voice AI with speech processing and conversation handling.
Hybrid Agents
Combined text and voice capabilities working together across channels.
Document & Data AI
Document Processing
Extract and transform data from PDFs, forms, and document workflows.
Data Analysis
Pattern recognition, insights generation, and automated data interpretation.
Content Generation
Automated content creation, summarization, and document generation.
Pre-Built AI Accelerators
Chat Agent Template
Battle-tested chat architecture based on 20+ production launches.
Voice Agent Template
Proven voice agent with telephony, speech processing, and production patterns.
Workflow Agent Template
Multi-step orchestration patterns with tool integration and error handling.
Full-Stack AI Integration
Connect AI capabilities to your existing platform, APIs, databases, and workflows. Complete system integration and custom development.
B2B SaaS Platform Development
Complete platform development – interfaces, APIs, databases, authentication, integrations, billing, and other foundational features.
Infrastructure & Deployment
Production deployment, monitoring, scaling, CI/CD pipelines, and security implementation for AI systems and SaaS platforms.
"We've built our entire B2B SaaS platform together, and I genuinely can't imagine working with anyone else"
— Ryan Tabb, Ex-Founder, Bullseye (Exited)
"Their transparency about AI capabilities has been crucial for making informed strategic decisions about our product."
— Kevin M.A. Nguyen, Co-Founder, Proximo AI
Here's how we work together:
Intro Call
We dig into your goals and challenges and figure out if we're the right fit. No sales pitch, but a honest conversation about what needs to happen.
"Softcery's approach is exceptionally thoughtful - they consider the complete business context, not just the immediate technical requirements."
— Kevin M.A. Nguyen, Co-Founder @ Proximo AI
Shaping Phase
We define exactly what gets built, document edge cases, and lock in timeline + budget. This is where we prevent the "6 months later..." nightmare.
"Softcery treated our project with the same care we would - validating every assumption and researching every angle before building."
— Charley Cohen, Director @ TIC.uk, Founder @ Ticitz
Build Phase
We deploy to production in the first weeks and iterate from there. Weekly updates, working functionality you can see and test immediately as we build.
"Softcery combines deep product strategy with technical execution - they don't just follow instructions, they challenge your approach and find better solutions."
— Ryan Tabb, Ex-Founder, Bullseye (Exited)
Launch & Scaling
We finalize the production system, document everything properly, and either hand off cleanly or stick around as your ongoing AI partner. Your choice.
"Softcery was fantastic throughout our re-build of a recently acquired B2B SaaS. Highly recommend in you are in need of high quality AI and SaaS engineering."
— Chris Riley, Acme Studio (Cuppa AI, Bullseye, Experts Ink)
Something brought you here. Let's figure out if we can help.
Download our AI Launch Plan to see the proven framework from 20+ AI launches, or schedule an intro call to understand what you're building and how we might help.
The Founder's Guide to AI Engineering
In-depth coverage of AI engineering for B2B SaaS founders. Analysis, technical breakdowns, and implementation guides from the field.
Agentic Systems
AI Agents Break the Same Six Ways. Here's How to Catch Them Early.
Works in staging. Fails for users. Six architectural patterns explain the gap, and all of them show warning signs you can catch early.
You Can't Fix What You Can't See: Production AI Agent Observability Guide
Failures you can't reproduce. Error logs that tell you nothing. Three observability pillars solve this: tracing, monitoring, and evaluation.
The AI Agent Prompt Engineering Trap: Diminishing Returns and Real Solutions
Founders burn weeks tweaking prompts when the real breakthrough requires a few hours of architectural work.
Choosing LLMs for AI Agents: Cost, Latency, Intelligence Tradeoffs
Demos work. Production reveals $47 conversations, 2-second pauses, unpredictable failures. Three dimensions help choose.
We Tested 14 AI Agent Frameworks. Here's How to Choose.
Your use case determines the framework. RAG, multi-agent, enterprise, or prototype? Here's how to match.
Voice Agents
How to Choose STT and TTS for Voice Agents: Latency, Accuracy, Cost
Every provider claims low latency and high accuracy. Real differences show up in production. Here's what actually matters.
Real-Time (S2S) vs Cascading (STT/TTS) Voice Agent Architecture
Both architectures work in demos. Different problems emerge in production. Here's what determines the right choice.
Choosing an LLM for Voice Agents: Speed, Accuracy, Cost
Fast models miss edge cases. Accurate models add 2 seconds. Cheap models can't handle complexity. Here's how to choose.
Why Voice Agents Sound Great in Demos but Fail in Production
Understanding why AI voice agents break down is the first step to building a solution that actually works in real life.
Testing Voice Agents: Methods, Metrics, and Tools
Controlled tests pass every time. Real users break agents with accents, noise, and bad networks. Here's what to test for.
Featured
Agentic Coding with Claude Code and Cursor: Context, Memory, Workflows
Agents go in circles without project context. The same agent ships production code daily with proper structure. Here's the system.
8 AI Observability Platforms Compared: Phoenix, Helicone, Langfuse, & More
AI agents fail randomly. Costs spike without warning. Debug logs show nothing useful. Eight platforms solve this differently.
US Voice AI Regulations: TCPA, BIPA, COPPA, HIPAA, & State Privacy Laws
Legal compliance sounds expensive and complex. Most voice AI startups need eight laws and a 5-step framework to ship safely.
11 Voice Agent Platforms Compared: Vapi, Ultravox, Retell, & More
Platforms promise easy setup. Production reveals control limits, concurrency caps, and cost scaling. Match your constraints before choosing.
SOC 2 for Voice AI Agents: Security, Confidentiality, and Quick Wins
Enterprise deals stall without SOC 2. Formal audits cost months and $50k+. Eight steps align your startup now before compliance blocks revenue.