SFDIFYGenerative AI development, shipped to real users.
SFDIFY is a generative AI development company. We design, build and run AI features in production: assistants, document automation, search and agents, wired into the systems you already use. AI runs inside our own products every day, so we build for what happens after launch.
Artificial intelligence development services.
AI features inside your product
Copilots, assistants and smart defaults added to an existing app or SaaS, with the model behind an API you control.
Document and data extraction
PDFs, emails and forms turned into structured records. Yolda reads trucking rate confirmations straight into loads.
Search and answers over your data
Retrieval over your documents, tickets or product data, with sources shown so people can check the answer.
Workflow automation with LLMs
Classify, summarize, route and draft inside the tools your team already uses, with a person approving what matters.
Custom generative AI apps
New web and mobile products where AI is the core feature, from the first version to production.
Evaluation, guardrails and cost control
Test sets, output checks, logging and model routing, so quality is measured and the model bill stays predictable.
From first call to launch.
Find the use case
Start from a real task and its numbers, and confirm AI is the right tool. The first consultation is free.
Prototype on your data
A working prototype against real examples, with a test set that defines what "good" means.
Build it into your stack
Production code, integrations, permissions, logging, and a fallback for when the model is unsure.
Launch, measure, improve
Ship to real users, watch quality and cost, and improve from what people actually do.
Built and run by SFDIFY.
Yolda
The AI-native TMS for trucking. Its AI reads rate confirmations into loads, watches every CDL and medical-card date, and answers questions about your numbers.
Learn moreUSTAXX
The portal and app behind an IRS-authorized e-file practice. Clients ask USTAXX AI, track deadlines and follow their return in nine languages.
Learn moreSegeo
Writes and publishes a useful blog post to a business's site every day and runs its Instagram. SaaS from $89 a month.
Learn moreMyCheck
A checklist app rated 4.8 on the App Store, in 13 languages. Saves checklists from ChatGPT, Claude, Grok or Gemini.
Learn moreQuestions, answered.
What does a generative AI development company do?
It designs and builds software where a large language model or another generative model does part of the work: drafting, extracting, answering or deciding. At SFDIFY that covers the product design, the model and prompt work, the integrations and the monitoring after launch.
Which AI models do you work with?
Mostly OpenAI, Anthropic and Google Gemini models, chosen per task for quality, speed and cost.
Can you add AI to software we already have?
Yes. Most AI projects add a feature to a product or workflow that already exists, through an API layer, rather than rebuilding it.
How do you keep AI output reliable?
Each feature gets a test set of real examples, checks on the output, logging, and a fallback or human review for cases the model is unsure about. Quality is measured before and after launch.
How do we start?
Book a free first consultation and describe the task you want AI to help with. We will tell you honestly whether AI is the right tool and what a first version would look like.
Further reading.
What Is AI Integration, and Does Your Business Need It?
What AI integration is, how it differs from using ChatGPT by hand, what drives its cost, and how to tell whether your business needs it yet.
Learn moreThe AI Integration Mistakes That Waste Time and Budget
Avoid common AI integration mistakes: fix the process first, define the problem, check data quality, pilot one workflow, train staff, and measure results.
Learn moreAI Integration: Build vs. Agency vs. Off-the-Shelf
Compare three AI integration paths (off-the-shelf tools, an in-house build or an agency partner) on cost, speed, customization and data control.
Learn moreHow to Build an AI MVP That Actually Attracts Investors
How to build an AI MVP that attracts investors: focus on one AI feature, use a proven stack, track outcome metrics and avoid common diligence mistakes.
Learn more