We help B2B SaaS companies ship production-grade AI agents, optimize LLM infrastructure, and build AI features that actually get adopted — with the engineering depth and operational rigor to deliver real business impact.
An example of the dashboards we build for leadership — real-time visibility into agent performance, adoption metrics, and business impact.
Whether you're shipping agents, driving AI adoption, or discovering agentic workflows — we bring the strategy, engineering, and operational rigor to make it real.
From prototype to production — we architect agent systems with tool use, memory, multi-agent orchestration, and the infrastructure to run reliably at scale.
Observability, tracing, drift detection, and custom eval suites so your agents improve over time — not degrade.
We study how your teams actually work — their tools, habits, and bottlenecks — then recommend AI solutions that fit naturally into existing workflows.
Rollout programs, hands-on training, champion networks, and adoption analytics that drive real productivity gains across your organization.
We go through your existing products and processes to identify which workflows are ripe for agentic automation and where the highest ROI lives.
Transform linear funnels into autonomous loops — designing the agent topology, feedback mechanisms, and human-in-the-loop checkpoints.
A proven approach that flexes across all three pillars — whether you need agents shipped, teams enabled, or workflows reimagined.
Deep-dive into your AI stack, team workflows, and product landscape. We map opportunities across productionization, adoption, and agentic automation.
Prioritized roadmap, system architecture, adoption plan, or workflow redesign — scoped to deliver measurable outcomes fast.
Hands-on delivery: shipping agents, deploying monitoring, running training programs, or designing agentic loops — whatever the engagement calls for.
KPI validation, knowledge transfer, runbooks, and a clear path forward so your team owns and evolves everything we build together.
Fulcrum AI was founded by an engineer who has built AI agent systems in production — including systems handling 200,000+ agent interactions per day — and worked on LLM inference optimization and model training infrastructure. That hands-on experience shapes everything we do. We are a remote-first consultancy serving B2B SaaS companies in India and the UAE.
We don't stop at architecture diagrams. We build, monitor, and iterate until your agents are production-grade and delivering ROI.
We match AI tools to how your people actually work — not how a vendor says they should. That's why adoption rates hold.
We find the funnels hiding inside your products that should be loops — then design the agentic systems to make it happen.
I'm a software engineer with 6 years of experience building AI systems in production. Before starting Fulcrum, I built production-grade AI agents at scale — including systems handling 200,000+ agent interactions daily — and worked on LLM inference optimization and model training infrastructure at leading technology companies.
I started Fulcrum from a simple conviction: most SaaS companies don't need another AI strategy deck. They need someone who can actually build — and stick around until the agents ship, the adoption numbers hold, and the system runs reliably at scale.
Our Belief
Fulcrum AI was born from a simple conviction: the best AI systems are the ones people actually use. We design every agent, every workflow, and every rollout from the perspective of the human who has to live with it daily. Our speciality is Human-AI cohesiveness — finding the path of least resistance between powerful AI capabilities and how real people work, so adoption happens naturally, not by mandate.
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| Service | Capabilities | Status |
|---|---|---|
| Agent System Design | Multi-agent orchestration, RAG pipelines, tool integration, memory & planning systems, production infrastructure | Available |
| Monitoring & Evals | LLM tracing, drift detection, custom eval suites, hallucination alerts, continuous quality monitoring | Available |
| Workforce AI Assessment | Employee work style analysis, tool-fit evaluation, bottleneck mapping, AI readiness interviews | Available |
| AI Adoption & Enablement | Rollout programs, hands-on training, champion networks, adoption analytics, change management | Available |
| Product & Workflow Audit | Process mining, agentic opportunity mapping, ROI analysis, workflow automation assessment | Available |
| Agentic Loop Design | Funnel-to-loop transformation, agent topology, feedback mechanisms, human-in-the-loop checkpoints | Available |
| Phase | Timeline | Deliverables |
|---|---|---|
| Discover & Assess | Phase 1 | AI stack assessment, workflow mapping, opportunity analysis, risk register |
| Strategy & Design | Phase 2 | Prioritized roadmap, system architecture, adoption plan, workflow redesign |
| Build & Enable | Phase 3 | Agent deployment, monitoring setup, training programs, agentic loop implementation |
| Measure & Transfer | Phase 4 | KPI validation, runbooks, knowledge transfer, evolution roadmap |
| Area | Experience | Detail |
|---|---|---|
| AI Agent Systems | Production-grade | Built agents handling 200,000+ interactions/day at prior employer |
| LLM Inference | Optimization | Latency & cost optimization for large-scale LLM serving |
| Model Training Infra | Cluster management | Training cluster setup, orchestration, and operations |
| Software Engineering | 6 years | Full-stack & systems engineering background |