~50K
Enterprise B2B sales teams running AI notetakers today. Every one has a memory problem.
For investors
Institutional memory is the new bottleneck in B2B sales. We own the layer.
Salency is a system of record for what your accounts actually told you — a structured, cited, queryable memory layer that every future revenue tool will inherit from. Below: what we're building, who's building it, and why this moat compounds.
Platform & moat
The structured memory layer for B2B sales accounts.
Salency is a system of record for what your accounts actually told you. Every call becomes durable, queryable context mapped to your product catalog, so the next rep, the next quarter, and the next pipeline review all inherit what was said — not what someone remembered to type.
The primitive is structured account memory. The loop compounds: every call makes every future call smarter, for every future rep on that account. Every feature we ship — handoff docs, objection libraries, renewal briefs, agent-drafted outreach — inherits from the same core graph. One primitive. Everything else is surface.
Data primitive
Structured account memory — cited, scoped, and compounding — is the input every future revenue tool will be measured against.
The wedge is the shape of the data. Contradiction pairs, pain evolution over time, confidence-ranked pain → product matches, cross-account pattern graphs. None of these fit a CRM row. Flatten any of them into a field and you kill the thing that makes Salency uncopyable. That’s why we sit on top of your stack, not inside it. Reps live in CRM for pipeline stages. Reps live in Salency for the qualitative layer — what the customer actually said, what contradicts what, which pains map to which products.
The uncopyable pair
Pain-product mapping plus contradiction detection, embedded in product-management workflows. Either alone is defensible for 6 to 9 months. Together, with workflow depth, switching cost is measured in quarters.
Market
A $100M ARR opportunity, on a graph we own.
Bottom-up
Capture target
0.5–1% in 3 years
250–1,000 teams × $50–100K ACV = $12M–$100M ARR.
Validation
Clay: $1M → $100M
AI sales tooling category proves the scale. Clay hit $100M ARR in 2 years (a16z-led Series C, $3.1B valuation).
Counterexample
11x.ai raised $74M on autonomous AI SDRs and lost 70–80% of customers. Autonomous bots without structured customer memory don’t hold the relationship. That’s the gap we fill.
Competitive landscape
Closest threats, and where the shape doesn’t fit.
No single competitor ships pain-product mapping plus contradiction detection plus handoff brief as an integrated stack. The gap is the shape of the join, not the individual capabilities.
WhoThreatWhy they’re not there yet
Gong75%Could ship “Gong Reactivate” as a $10–20/seat add-on. Their focus is forecasting and coaching. Pain-product mapping is not their customer motion.
Clari + Salesloft50%$450M combined ARR (merged Dec 2025). Call intelligence plus forecasting. Pain-timing is their natural expansion, but their account is stage and number, not qualitative shape.
HubSpot Breeze50%200K customers, freemium. Could bundle pain-product mapping into Sales Hub — but bundling into a CRM flattens the graph, which is the thing that defends the wedge.
Salesforce Einstein45%150K customers. Could bundle for free. Slow to move, but devastating if they do. Same flattening problem as HubSpot.
AskElephant35%Closest on handoff docs. $99/mo anchor, 500+ teams, strong G2. Doesn’t hold state between handoffs, and doesn’t map pains to a product catalog.
03.
Why this team, on this problem, now.
HT
Howard TamCo-founder & CEO
Five founding-AE / BD seats in four years. Ran the HubSpot→Monday CRM migration at Sequence.
NI
Nikki IpCo-founder & COO
Data analyst at Adaptavist Group. Three years running operational reporting across HubSpot, Snowflake, DBT.
BO
Babajide OkusanyaFounding Engineer
Scaled MakersValley from 0 to $2M ARR (6.5y, NYC). Ships provenance-tracked AI context systems.
SG
Shristi GartaulaFounding Designer
Shipped Salency’s V1. Five years enterprise B2B design — Index Exchange, Myplanet, StatysTech.
Roadmap
What ships next.
V1.5 · Q2–Q3 2026Capture + push
- Recall.ai meeting bot — joins Zoom, Meet, Teams directly. Extraction without a transcript upload step.
- CRM push to Monday and HubSpot — flat summary fields write back so reps don’t double-enter.
V2 · Q4 2026Enterprise readiness
- Salesforce and HubSpot native sync — the two buyers that sign the enterprise contract.
- Gong API transcript pull — turns Salency into the layer sitting on top of the most-entrenched input pipe.
- 10 paying customers, $50–100K ACV range.
V2.5 · 2027Scale decision
- $10–30M ARR target. Workflow integration depth (Productboard / Aha / Jira) locks switching cost to quarters, not weeks.
- Decision point: raise at the category-leader mark, or walk a profitability path into the expanded surface.
Why now
The bottleneck is about to shift.
Sales teams are consolidating tools and cutting rep headcount while deal complexity keeps rising. The surviving reps own more accounts with less tribal knowledge, and AI agents will start drafting their outreach inside the next eighteen months.
Both of those depend on structured account memory as the input — not a raw transcript pile, not another CRM field. The agent doesn't know what the buyer has already told you. The rep inheriting the account doesn't either. The asset that makes either one useful is the same asset.
Every LLM commoditizes extraction. What doesn’t commoditize is the customer-built graph of pains, products, and contradictions — and that graph compounds per customer, per call. The moat is the data shape, not the model.
Salency owns that layer. The longer a team runs it, the more context compounds — and the deeper the graph gets.