We build enterprise AI agents that automate complex workflows, accelerate decision-making, and generate measurable ROI. From intelligent document processing to autonomous sales assistants, our PhD ML engineers design agents that work the way your business actually operates.
We build custom AI systems that deliver measurable ROI for established companies. Production-grade solutions built by engineers who've shipped 150+ AI projects. Purpose-built systems around your data, your workflows, and your team.
Amerit Fleet Solutions automated their entire repair order review process, eliminating manual errors and freeing their team for highervalue work.
Protect Line's conversational AI agent routed complex insurance queries safely and accurately, adding $5M in new revenue in the first year.
Our proven process takes you from initial workshop to a production-ready AI agent in 12 weeks or less.
We design agents for the workflows that cost you the most, and engineer them to handle those processes reliably, at scale.
AI agents that independently execute multi-step business processes, from triaging support tickets to processing insurance claims. They follow your business rules, escalate edge cases to humans, and get smarter with every interaction.
Internal agents grounded in your proprietary data that give accurate, source-cited answers instead of hallucinated responses. Protect Line's agent generated $5M in incremental revenue by routing complex insurance queries safely.
Agents that read, understand, and act on complex documents at scale, from invoices and contracts to regulatory filings. Amerit Fleet Solutions automated 90% of repair order reviews, eliminating manual errors.
With strict role-based access control (RBAC), every agent only accesses the data it needs. For HIPAA, PCI DSS, or SEC-regulated industries, compliance is built into the architecture from day one — not added after the fact.
Our agents connect directly to your tools through APIs and Model Context Protocol (MCP) — Salesforce, HubSpot, Slack, SAP, Jira, custom databases, and more. No new platform. No disruption to how your team works.
Every line of code, every trained model, and every custom knowledge base is deployed into your own cloud infrastructure. No licensing fees. No vendor lock-in. No dependency on our platform to keep your agents running.
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Our process starts with connecting you to our leaders, who have built over 150 projects. If aligned, the second call will include our Product Managers and Engineers to scope the project. The final step is a proposal presentation.
We start by immersing ourselves in your business, industry, and existing software. We then build a functional proof-of-concept to validate the technical feasibility. This hands-on planning process arms you with a clear architectural blueprint and a precise technical implementation roadmap for the next phase.
Production-grade AI software, built in your infrastructure, with real-time visibility into every task. No prototypes, no maybe's. Just code that delivers testable ROI. We trademarked Full Transparency Development ™ , so you’re never left in the dark.
Go live, measure results, and scale AI across your organization at a predictable cost. We build with the right guardrails and measure KPIs on real results. We train your team to operate and manage what we developed, or we can provide ongoing maintenance and support.
The most impressive thing was their versatility and breadth of knowledge about our industry.
PM was amazing. They were on top of everything and kept the project moving very quickly.
The 923 team was fantastic to work with and taught me a lot about ML and AI.
A chatbot follows prescripted conversation flows. An AI agent reasons, plans, and takes action autonomously. Where a chatbot answers a FAQ, an AI agent can research across multiple data sources, make a recommendation, execute a workflow step, and follow up — all without human intervention. Think of it as the difference between a phone tree and a skilled employee who works 24/7.
Most enterprise AI agents go from discovery to production in 12 weeks or less. Week one is our AI Discovery Workshop. Weeks two through five focus on validation and architecture. Weeks six through twelve are dedicated development and integration.
Enterprise AI agent projects typically range from $150K to $600K depending on complexity, integration requirements, and data infrastructure. The engagement begins with a paid Discovery Workshop, followed by a Rapid Validation Sprint to prove feasibility before you commit to a full build.
Yes, 100%. Everything we build is deployed into your own cloud infrastructure. You retain full ownership of the code, trained models, and custom knowledge base. No ongoing licensing fees. No dependencies on our platform.
We use a multi-layered approach: RAG architecture grounds every response in your verified data, our 27-point evaluation suite tests for accuracy before deployment, human-in-the-loop escalation paths handle edge cases, and continuous monitoring improves accuracy over time.
Absolutely. We build agents that connect to your existing tech stack through APIs and Model Context Protocol (MCP). Common integrations include Salesforce, HubSpot, Slack, Microsoft Teams, SAP, Jira, and custom databases.
NineTwoThree is SOC 2 Type II certified, with independently audited data handling processes. Your data is never used to train external models. For healthcare, financial services, or government, we build HIPAA, PCI DSS, and other compliance requirements directly into the agent architecture.
Deployment is the beginning. We provide monitoring dashboards, ongoing performance optimization, and a clear expansion roadmap. The infrastructure built for your first agent serves as the foundation for new capabilities across departments with each subsequent agent delivered faster and at lower cost.
Build a new platform, or add AI capabilities to existing software, we deliver solutions that work in real operational environments.
Meet with founders Andrew Amann & Pavel Kirillov
Custom AI implementation roadmap
No sales pressure
