MULTI-AGENT AI SYSTEMS
Production-Grade AI That Actually Runs —
Not Demos
We design and ship multi-agent AI systems that automate real business workflows.
If you already tried AI demos, pilots, or single-model solutions — and they broke the moment reality hit — this is for you.
Built for startup teams from Seed to Series B that need real systems, not experiments.
Trusted for: production deployments · regulated environments · startup teams · full IP ownership
The real problem
AI demos are easy. Production AI is hard.
Why most AI projects fail:
AI doesn’t fail because it’s “too early.” It fails because systems aren’t designed to survive reality.
That’s what we build.
What We Actually Build
Autonomous AI systems that execute work
— end to end
We design multi-agent architectures where each agent has:
The result:
Workflows that scale without linear headcount growth — and can be owned by your team.
Designed for real teams. Not PhDs.
Not science projects.
What this enables
Multi-Agent Systems can — today:
Built for real constraints — built to ship.
Real use cases
⏱ Production in 8–10 weeksIntelligent Document Processing
Most requested by Series A teams
Learn moreThe problem
Manual document review is slow, expensive, and error-prone.
What we ship
Intake → Classification → Extraction → Validation → Human Review
Results from recent deployments
- •~70% reduction in processing time
- •95%+ extraction accuracy
- •10× throughput increase
⏱ Production in 10–12 weeksResearch & Analysis Automation
Fastest ROI
Learn moreThe problem
Analysts spend more time gathering information than analyzing it.
What we ship
Research agents: Gather → Verify → Synthesize → Write
Results
- •5× faster research cycles
- •Consistent structure and quality
- •Full source attribution
Why Multi-Agent Systems
TL;DR: single-model AI breaks under real workflows. Agents don’t.
Single-model systems fail when workflows:
Multi-agent systems solve this by design.
How We Ship (From Kickoff to Production)
We ship narrow, production-ready systems — not bloated platforms.
~2–3 hours per week from your team.
Technology
We choose tools based on outcomes — not trends.
Used where they make sense. Combined only when required.
RAG Architectures — the 16 we build with
Not “we do RAG.” Sixteen architectures, and the judgement to pick.
The 16 aren't exclusive — in production they compose. Retrieval variants (Hybrid, HyDE, Graph) are orthogonal to control variants (Agentic, Self-RAG, Recursive) and to deployment ones (Federated, Streaming, Modular). We start at Standard + Hybrid + Contextual and escalate only when the task justifies it: cost per query grows 3–10×.
Ownership & Governance
You own everything we build.
Designed to pass legal, security, and engineering review.
Pricing
Project-based pricing. You pay for results — not hours.
Starter — $15K–$25K
First production use case
→ Often pays back through immediate cost reduction
Learn more
Standard — $30K–$50K
Core business automation
→ Sustained operational impact
Learn more
Enterprise — $75K–$150K+
Mission-critical systems
→ Scale, resilience, governance
Learn moreMost teams start with one narrow workflow.
Why FACTA
We’ve shipped this before — that’s why it works.
Ready to solve a real use case?
30-minute working session No pitch. No sales deck. Just problem-solving.
Discuss Your Use Case✓Response within 24h
✓NDA available
✓Technical founder on the call
✓We’ll tell you if multi-agent AI is not the right solution