# Pre-Call Brief: Engineering Firms

**Vertical:** Geotechnical, structural, consulting engineering
**Last updated:** 2026-07-22
**Oction Labs**

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## 1. Target Buyer Profile

| Attribute | Specification |
|-----------|---------------|
| **Firm size** | 30-300 staff (mid-market entry) |
| **Job titles** | Managing Principal, Practice/Operations Director, CTO or Digital Lead |
| **Decision authority** | Managing Principal signs; Ops Director drives evaluation |
| **Sub-verticals** | Multi-discipline consulting, structural, civil, geotechnical |

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## 2. Primary Pain Points

1. **Senior engineers lose hours hunting prior calcs, specs, and standards interpretations** buried in shared drives, email threads, and retired staff's heads.
2. **Proposals take too long** — slow turnaround loses bids against faster competitors.
3. **Knowledge walks out** with every departing principal; 30 years of judgment evaporates.
4. **Two document systems after a merger** — neither talks to the other; staff use the wrong precedents.

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## 3. Bleed Calculation Example

10 engineers x 5 hrs/week searching at ~$250/hr loaded = **$650,000/year** of billable capacity burned on searching instead of engineering.

*Confirm live: How many engineers spend how many hours per week hunting for prior work? What is their loaded hourly rate?*

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## 4. Key Questions to Ask

1. "How do your engineers find prior calculations and precedent details today?"
2. "What happens when a principal with 20+ years leaves — where does their knowledge go?"
3. "How long does it take to assemble a proposal from your past winning work?"
4. "Have you merged with or acquired another firm recently? How do staff know which precedents to use?"

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## 5. Proof Points to Share

- **74% correct retrieval** with grounding vs ~5-10% without
- **0% fabrication** on trap questions in our measured test set
- **Cited answers** — every response references the source document
- **Sovereign deployment** — data never leaves their infrastructure

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## 6. Objections Likely to Hear

| Objection | Response |
|-----------|----------|
| "We already have a document management system." | "Where does knowledge go when the document system doesn't know the question? We add queryability to what you already have." |
| "Our clients require sealed drawings; we can't use AI." | "The AI doesn't draw. It retrieves and cites. Every engineering judgment stays human." |
| "Engineers won't trust machine answers." | "They don't have to trust. They verify — with the cited source document attached to every answer." |

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## 7. Relevant Case/Example

A 45-person structural firm has 18 years of drawings, calculations, and client RFIs in shared drives. A senior engineer asks, "How did we detail the pile cap on the 2023 riverfront job and why?" The system returns the specific drawing, the engineer's note, and the standard interpretation — in 8 seconds instead of 45 minutes hunting through folders.

*Illustrative scenario. Not a client result.*

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## 8. Recommended Pricing Tier

| Firm Profile | Tier | Pricing |
|--------------|------|---------|
| Single-office, 30-80 staff | Standard | $25,000 initial + $10,000/month |
| Multi-office, 100+ staff, complex integrations | Enterprise | $200,000 initial + $20,000/month |

Add-ons to mention: Expertise interview program ($2,000/person) for departing principals.

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## 9. Talk Track Opening

"You're losing senior engineer hours to document hunting. We install a private knowledge system that lets staff ask questions in plain language and get cited answers from your own precedents — no data leaves your building. Can I ask how your engineers find prior calculations today?"

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## 10. Competitors in This Space

- **Traditional:** Document management vendors (Aconex, SharePoint consultancies)
- **AI-native:** Generic enterprise RAG vendors; public AI tools (ChatGPT, Claude) — emphasize the privilege/sovereignty gap
- **Professional services:** Big Four tech consulting — emphasize speed and specialization

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*eight agents. one organism.*