Your enterprise data
wasn't built for agents.
We modernize both.
Most enterprise AI initiatives stall because the data platform wasn't designed for it — batch pipelines, siloed warehouses, inaccessible knowledge. Factiveminds modernizes your data infrastructure and deploys production-grade agentic systems on top.
Senior AI and data engineers embedded in your team. Production outcomes, not prototypes.
Enterprise engagements
Built the Homoeopathic Clinical Case Repository (HCCR) — an AI-powered knowledge platform enabling healthcare professionals, researchers, and students to search high-volume clinical case data across all disciplines, surfacing clinically important information at scale.
Modernized the data platform and deployed AI-driven analytics agents across Southeast Asia's leading pharmaceutical and nutrition enterprise — unifying decision intelligence across a multi-company portfolio spanning consumer health, pharma, and nutrition.
Two Practices. One Team.
End-to-End Delivery.
Agentic AI and data platform modernization are inseparable. We cover both — from legacy pipeline architecture through multi-agent production systems. No handoffs between teams.
Multi-Agent Systems
Orchestrator and specialist agent architectures engineered for enterprise production — typed agents, human-in-the-loop controls, full observability, and audit trails your compliance team can live with.
RAG & Knowledge Systems
Ground your agents in your own enterprise knowledge — not the internet. Standard RAG for document retrieval. GraphRAG for complex multi-hop reasoning over proprietary knowledge graphs.
Ontology & Enterprise Knowledge Graphs
Build the semantic backbone your agents reason over. We design domain ontologies and enterprise knowledge graphs — connecting entities, relationships, and business rules across silos so agents can traverse your data with the precision of a domain expert.
LLM Integration
Connect LLMs to your enterprise systems — CRMs, ERPs, internal tools, and proprietary APIs. Structured outputs, tool use, and enterprise security controls built in from the start.
AI Observability & Governance
Drift detection, hallucination monitoring, decision audit trails, and incident playbooks — wired into your agents before something breaks in production. Enterprise-grade governance from day one.
Lakehouse Architecture
Migrate from fragmented legacy warehouses and siloed data marts to a unified lakehouse — built to serve both BI and AI agents. Delta Lake, medallion architecture, and semantic layers that agents can query.
Real-Time Data Pipelines
Replace batch-first architectures with event-driven pipelines — so your agents act on current data, not yesterday's. Change data capture, streaming ETL, and low-latency serving layers for agentic workflows.
Data Quality & Governance
AI is only as good as the data underneath it. We instrument data contracts, lineage tracking, automated quality checks, and access governance — so your agents don't hallucinate because the data was wrong.
AI-Ready Data Platform
Build vector stores, feature stores, and agent-accessible APIs on top of your modernized platform. The final step: a data layer purpose-built to serve retrieval-augmented agents at enterprise scale.
Enterprise AI Strategy
Use-case discovery ranked by ROI across your operations. A costed, prioritized path from your current state — legacy data stack and all — to production AI agents. Not a generic framework.
AI Architecture Review
An independent assessment of your current data platform and AI infrastructure. We surface the gaps that will block agentic AI at scale — before you build on top of them.
Engineering AI Accelerator
A 3-week immersive that embeds AI into how your engineering team builds software — on your real stack, real backlog. Measured cycle time improvement. Capability that stays when we leave.
Agents need real-time, governed,
agent-accessible data to be useful.
Most enterprises don't have that yet.
We close that gap. Data platform first, agents on top — delivered as one integrated engagement, not two separate projects handed off between teams.
Experiment phase is over.
Now comes accountability.
76% of developers use AI daily. The productivity gain for most teams? 3–5%. The teams that break out don't use AI differently — they think about it differently. We coach enterprise engineering teams there, on real production work, with their actual stack.
- AI instructions and modes tuned to your tech stack, repos, and architecture
- Portable workflow playbook — AI across every SDLC phase
- Before/after metrics report: cycle time, test coverage, confidence
- A team that owns the system when we leave
Senior Engineers. Full Stack.
No Lock-in.
We've seen how the big consulting firms approach enterprise AI. We built the alternative.
Built, Not Just Planned
Strategy without execution is just paper. We design, build, deploy, and measure — every engagement ends with something running in your stack, not sitting in a document.
Full Stack — Data + Agents
We cover the full AI value chain: from raw data infrastructure through agentic applications. No handoff between a "data team" and an "AI team." One engagement, end to end.
Senior Engineers, Always
Named senior AI and data engineers embedded in your sprints. Not a partner who sells and disappears, replaced by juniors. Minimum 10+ years of real production experience, enterprise context.
Capability Transfer, Not Dependency
When we leave, your team can run, extend, and debug everything we built. Full documentation, runbooks, and hands-on transfer. We measure success by how little you need us after.
Assessment to Production in Weeks
Most enterprise AI projects take quarters to show ROI. Ours are scoped to ship faster.
Architecture Assessment
30-minute discovery call, then a structured review of your data platform and AI readiness. We arrive prepared. You leave with a clear gap analysis.
Week 0 — Complimentary
Modernization Blueprint
We map your highest-ROI data platform moves alongside the agentic AI use cases they enable. One integrated roadmap. Costed and sequenced. Not a 50-slide deck.
Week 1
Build & Ship
Senior engineers embedded in your stack — modernizing pipelines and deploying agents in parallel. Production-standards from sprint one, with your team alongside throughout.
Weeks 2–8+
Operate & Scale
Before/after measurement, full documentation, observability dashboards, and hands-on capability transfer. Your team runs it independently from handover day.
Week 8 onwards
Your Data Platform + Agents,
Engineered for Production.
Book a complimentary architecture assessment. We'll review your data infrastructure, identify what needs modernizing, and show you where agentic AI creates the most enterprise value. No commitment. No slide deck.
Response within 1 business day · Senior engineers on every engagement