What worked at 20 people breaks at 100. AI rebuilds it before 500.
You have product-market fit and capital. Now you need the operational backbone that keeps pace with revenue instead of breaking every time it triples.
Working systems in weeks. Built lightweight enough to iterate on, robust enough to survive your next 10x.
The processes that worked at 20 people are breaking at 100.
These aren't people problems. They're architecture problems.
Manual handoffs everywhere
Sales closes a deal, then pings CS in Slack, who creates a ticket, who updates the spreadsheet. At 50 customers it's annoying. At 500 it's a churn driver.
Tool sprawl and data silos
HubSpot for sales, Intercom for support, Notion for docs, Jira for eng, spreadsheets for everything else. Nobody has a unified view. Your "data strategy" is copy-paste between tabs.
Board asked for metrics you can't produce
NRR, pipeline coverage, activation time: the board wants them monthly and your team scrambles to assemble them from 4 different tools every time. Or you're reporting numbers you don't trust.
Every team is asking for more ops capacity
CS needs renewal coordination. Sales needs rev ops. Finance needs reporting. Each need is real. Together they signal that the ops infrastructure isn't scaling, and people are being asked to do work a system should carry.
Customers are churning before they activate
Onboarding takes 3 weeks. Customers go quiet after week one. By the time CS follows up, they've already decided it's not working. You can't white-glove every account at scale.
Person problem or system problem?
The question to ask about every operational bottleneck: does it need judgment, or does it need a system? If the work is repetitive, data-driven, and follows rules, it's a system problem, and your people should be freed from it.
Give it to a system
Customer onboarding workflows. Renewal tracking and outreach triggers. Support ticket routing and first-response. Sales data enrichment and follow-up sequencing. Board deck data assembly. Vendor management and contract tracking.
These are systems problems. AI handles them at any scale.
Keep it with people
Strategic customer relationships. Complex negotiations. Product decisions. Team leadership. Creative problem-solving. Anything that requires judgment, empathy, or navigating ambiguity.
These are people problems. This is where your team's time should go.
Build the operational backbone before you need it.
The first 30 days
We audit your operational workflows, map the handoffs that break at scale, and identify the 3–5 automations that create the most leverage. Then we build the first one. You have a working system before the month is out.
- Operational scalability audit across your stack
- Process automation prioritization by leverage and internal lift
- First automation deployed and running (typical: 2–3 weeks)
- Build-vs-buy framework for HubSpot, Intercom, Jira, and similar tools
Internal lift required: one ops/eng point of contact, 2–3 hours/week for the first month. We handle implementation.
Ongoing implementation
We ship working AI systems that integrate with your existing tools: HubSpot, Intercom, Slack, Jira, whatever you run. Lightweight enough to iterate on, robust enough to handle 10x your current volume.
- Customer lifecycle automation (onboarding through renewal)
- Revenue operations and pipeline intelligence
- Internal tooling and data pipelines
- Board reporting and investor update automation
We built Soligence as an AI-native company from day one.
CRM: thousands per month → a fraction of the cost
Zero manual data entry. All interactions captured automatically. Natural language access to full client history. Our CRM costs less per year than most startups spend per month on enterprise seat licenses.
Board prep: 2 days → 2 hours
Financial data, pipeline metrics, and operational KPIs pulled from live sources and assembled automatically. Commentary drafted by AI. Our team reviews and edits instead of building from scratch.
Show us what's breaking. We'll show you what to automate first.
Tell us your stage, team size, and the operational pain that keeps you up at night. We'll map the 3–5 highest-leverage automations and build the first one in weeks.
Intro call
30 to 45 minutes. You describe the bottleneck; we tell you honestly whether AI is the right lever and what discovery would cover. No deck, no pitch.
Discovery
Two to four weeks. We map the workflows, data, and controls, baseline the value, and return a scoped plan with timeline and pricing. Starts at $5K, credited in full toward project work that begins within 60 days.
Project work
Argus360 for the core customer and deal intelligence, custom builds by our AI Factory for what a module does not cover. Structured the way you and we agree is best: a fixed-scope sprint, a multi-phase build, an ongoing operations partnership, or fractional AI leadership.
Most engagements follow this pattern. See how we work.
Sources
1. Stanford Institute for Human-Centered AI, Artificial Intelligence Index Report 2026, April 2026: measured productivity gains of 14% to 15% in customer support and 26% in software development.