Agentic AI Capabilities

Velocity's comprehensive suite of Agentic AI services — powered by our Trogo.AI platform. From custom AI agents and model fine-tuning to RAG systems and workflow automation, we deliver enterprise-grade AI solutions that think, learn, and act autonomously to transform your business operations.

Explore Our AI Services
150+
AI Projects Delivered
50+
Enterprise AI Clients
6
Core AI Capabilities
18+
Years Tech Experience

Our AI Capabilities

Six core competencies that cover the full spectrum of enterprise AI needs

Custom AI Agents

Intelligent autonomous agents that reason, plan, and execute complex tasks — from customer support and document processing to DevOps and sales qualification. Learn more →

Model Fine-tuning

Transform general-purpose LLMs into domain experts with your proprietary data. LoRA, QLoRA, and full fine-tuning with custom evaluation suites and production deployment. Learn more →

AI Workflow Automation

Replace brittle rule-based automation with intelligent AI workflows that handle exceptions and adapt to changes — document processing, decision automation, and cross-system orchestration. Learn more →

LLM Integration

Production-grade LLM integration with multi-provider abstraction, security guardrails, cost optimization, and enterprise-level reliability at scale. Learn more →

RAG Solutions

AI systems grounded in your proprietary data with cited, verifiable answers. Semantic search, document-level permissions, and continuous knowledge sync. Learn more →

AI Training & Consulting

Executive strategy sessions, developer workshops, AI roadmaps, vendor evaluations, and ongoing advisory. Build internal AI capabilities that last. Learn more →

The Velocity AI Advantage

What sets our AI practice apart from pure consultancies and research labs

We Build, Not Just Advise

Enterprise Security First

18+ Years Delivery Track Record

Full Stack AI Capabilities

Measurable ROI Focus

From PoC to Production Fast

End-to-End AI Transformation for a Financial Services Firm

A mid-size financial services company came to us with a mandate from their board: "Figure out AI." They had no AI team, no clear use cases, and were overwhelmed by vendor pitches. Over 12 months, we delivered a complete AI transformation.

Phase 1 (Month 1-2): AI strategy assessment — identified 12 potential use cases, ranked by ROI and feasibility. Phase 2 (Month 3-4): Built 3 proof-of-concepts for the top opportunities. Phase 3 (Month 5-8): Deployed an AI-powered customer onboarding agent, a document processing workflow for KYC compliance, and a RAG system for internal policy queries. Phase 4 (Month 9-12): Trained their engineering team to maintain and extend the systems. Result: $3.2M in annual operational savings and an internal AI team capable of delivering their own projects.

End-to-End AI Transformation for a Financial Services Firm

AI-Powered Product Suite for a SaaS Company

A B2B SaaS company wanted to add AI features to differentiate their product but wasn't sure what would resonate with customers. Their competitors had all added "AI" to their marketing but most features were shallow chatbots.

We started with customer research to identify genuine pain points, then built 5 AI features: intelligent document analysis, automated report generation, predictive analytics dashboards, natural language data querying, and smart notifications. The LLM integration layer we built allows their product team to add new AI features in 1-2 weeks. Within 6 months of launch, AI features became the #1 reason cited by new customers for choosing their product. Churn decreased 23%.

AI-Powered Product Suite for a SaaS Company

Manufacturing Intelligence Platform — 30% Defect Reduction

A manufacturing company with 12 production lines needed to reduce quality defects without slowing throughput. Traditional statistical process control caught problems too late — after defective batches were already produced.

We deployed a multi-agent AI system: monitoring agents analyze sensor data from each production line in real-time, prediction agents forecast quality issues 30 minutes before they occur, and optimization agents recommend parameter adjustments to prevent defects. The system integrates with their MES (Manufacturing Execution System) and sends alerts to floor supervisors with specific corrective actions. Defect rate dropped 30% in the first quarter while throughput increased 8%.

Manufacturing Intelligence Platform — 30% Defect Reduction

AI Capabilities FAQ

Start with a focused assessment of your highest-pain business processes. We typically recommend beginning with a 2-week discovery engagement where we interview stakeholders, evaluate your data infrastructure, and identify the 2-3 use cases with the best combination of business impact, data readiness, and implementation feasibility. This gives you a clear, prioritized starting point rather than trying to boil the ocean.
A focused proof-of-concept can demonstrate value in 2-4 weeks. A production deployment of a single AI feature typically takes 6-12 weeks. Enterprise-wide AI transformation is a 6-18 month journey. We structure engagements to deliver incremental value — you see working AI solving real problems within the first month, not just a strategy deck.
No. Many of our clients start with zero in-house AI expertise. We handle the full build and deployment, then train your team to maintain and extend the systems. Over time, we help you build internal AI capabilities through knowledge transfer, training programs, and paired development. The goal is to make your team self-sufficient, not dependent on us.
Security is foundational, not an add-on. We implement PII detection and redaction, encrypt data in transit and at rest, support on-premise and private cloud deployments, provide complete audit logging, and comply with HIPAA, SOC 2, GDPR, and other regulatory frameworks. For the most sensitive use cases, we deploy self-hosted models so no data ever leaves your infrastructure.
We build and deploy AI systems in production every day — we're not just advisors who hand you a report. Our 18+ years of software engineering experience means we understand how AI fits into real enterprise architectures, not just how it works in a lab. We also maintain everything we build, so we're invested in long-term success, not just the initial engagement.
We offer three engagement models: (1) Fixed-price projects with clear scope and deliverables. (2) Time-and-materials for exploratory work and ongoing development. (3) Monthly retainers for advisory and support. Most clients start with a fixed-price PoC or assessment, then transition to ongoing development. We're transparent about costs — no hidden fees or surprise overages.

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