Aware GTM · Product Portfolio

What we build, what we give away, and what we deliver.

Aware operates a four-tier portfolio. Free utilities seed the ecosystem. The platform is what we run on. Data products convert. Productized services are what we deliver hands-on. Click any card to flip it.

01 · Free Utilities
02 · GTM Operating Stack
03 · Data & Enrichment
04 · Productized Services
01
Free · Ecosystem on-ramps

Free Utilities

Tiny tools we give away to the GTM-engineering community. No monetization intent — they exist to bring people into the Aware orbit. Each one solves a sharp, narrow pain that any operator using Clay or running a calendar feels every week.

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Tally
Cross-row visibility for Clay
Live
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Tally
Free utility · Clay ecosystem

Problems it solves

  • Clay runs row-by-row — there's no native rank, percentile, or cohort comparison across the table
  • Operators export to Sheets to rank, then re-import — fragile and slow
  • Score-based logic falls back to absolute thresholds when relative position is what you actually want

How it works

  • HTTP in, HTTP out. Clay sends scores, Tally returns the row's rank, percentile, and top-N flag — Clay branches off it
Built for Clay power users, GTM engineers, RevOps teams running scoring or ICP-fit models. Live at tally.tryaware.ai.
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ClaySON
JavaScript on tap, for Clay
Concept
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ClaySON
Free utility · Clay ecosystem

Problems it solves

  • Clay's formula language hits a wall on real string / date / math gymnastics — and AI columns are overkill (slow, non-deterministic, burning credits) for logic that's just code
  • Standing up a Lambda or a Cloudflare Worker for a 4-line transform is hours of yak-shaving for a 30-second function
  • Glue logic ends up copy-pasted across columns and tables — no shared runtime, no version control, no single place to fix a bug

How it works

  • HTTP in, JSON out. POST a JS function body plus inputs to ClaySON's endpoint; a sandboxed runtime executes it and returns the result. Save a function under a stable URL to call it by name across Clay tables.
Built for Clay power users, GTM engineers, RevOps teams doing deterministic data plumbing — without the serverless tax.
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Fewtimes
Three slots, pasted, done
In Build
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Fewtimes
Free utility · giveaway brand

Problems it solves

  • Pulling 3 calendar slots manually breaks flow — you context-switch, eyeball, and type
  • Multi-calendar busy time (work + personal + iCloud) is hard to merge by hand
  • Team availability requires juggling several free/busy views to find a slot where everyone's open

How it works

  • macOS menubar app. Type /fewtimes anywhere. Three free slots paste at the cursor. iOS via Shortcut.
Built for anyone who books meetings — sales, recruiters, founders, operators. Free. Owns its own brand at fewtimes.com.
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[ md ]
emdee
Collab markdown for clients
Concept
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emdee
Free utility · Collab markdown

Problems it solves

  • Sharing markdown drafts with clients is rough — Notion is heavy, Google Docs murders code blocks and structure
  • Client-facing doc collab needs a lower bar than a full wiki, but more than a one-shot link
  • GTM-engineering work lives in markdown — the review surface should respect that

How it works

  • TBD. Likely a shareable editor with comments and version snapshots. Designed for the "send the client a draft" moment.
Open questions: name, scope of editing/commenting, whether there's a lightweight branded-link layer for clients.
02
Platform · What we run on

GTM Operating Stack

The platform Aware itself uses to deliver client work, and that we license to other GTM engineers, agencies, and in-house RevOps teams. Both products are battle-tested through our own services engagements before they go to market.

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Kernel
Source of truth for AI workflows
Beta
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Kernel
Platform · context infrastructure

Problems it solves

  • Context drifts across Clay, ChatGPT, n8n, agents — teams re-paste the same ICPs and personas everywhere
  • RAG/vector setups are overkill for static reference content; modern context windows fit a curated doc
  • SMEs who own the prompt source can't see where (or whether) it's being consumed downstream

How it works

  • Drop sources in. Generate a versioned Anchor Context Document. Pull it via stable API URL into anything that speaks HTTP.
Built for GTM agencies, RevOps, AI/automation leads at B2B SaaS. Live at kernel.tryaware.ai.
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Daloop
Quality control for AI outbound
Live
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Daloop
Platform · sales engagement / AI QA

Problems it solves

  • AI made it easy to generate outbound at scale — but not better outbound. Inbox noise is up, conversion is flat
  • Manual review in spreadsheets is brittle; sales leaders can't enforce voice or quality at scale
  • Multi-channel sequences drift in tone — message-by-message review misses the bigger picture

How it works

  • Design → Push → Review. Full-sequence inline review, CRM-native (HubSpot live), builder-agnostic via API. Edits feed back into the AI prompt loop.
Built for B2B sales teams running AI outbound (especially Clay), RevOps. Live at daloop.tryaware.ai.
03
Data · What we commercialize

Data & Enrichment Products

Niche datasets that sit in the seam between "hard to assemble manually" and "not yet trivial for an agent to reconstruct on demand." A 1–2 year window of value while public sources stay messy. Each one serves a sharp vertical.

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FranInfo
Franchise data, decoded
In Design
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FranInfo
Data · franchise intelligence

Problems it solves

  • FDD (Franchise Disclosure Document) data is locked inside hundreds of PDFs across state portals
  • Researching a franchise system takes hours per target — fees, royalties, unit counts, litigation history all need stitching
  • No clean programmatic access for outbound, M&A research, or supplier prospecting into franchise systems

How it works

  • Structured, queryable FDD data via API and UI. Designed to feed Clay tables, deal databases, and outreach systems directly.
Built for sales into franchise systems, suppliers to franchisees, M&A researchers, brokerage networks.
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W I
Untitled
Wealth & insurance broker data
Concept · Unnamed
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Untitled — Brokers
Data · wealth & insurance broker enrichment

Problems it solves

  • Broker data is fragmented across regulators — FINRA BrokerCheck, SEC IAPD, state insurance departments, IIROC, MFDA — each with its own format
  • Tracking broker movements (firm switches, BD transitions, license changes) requires manual scraping per regulator
  • No clean enrichment for vendors selling into broker networks (advisor tech, planning, CRM, recruiting), or for B2B prospecting where the broker is the target

How it works

  • Aggregated, normalized broker dataset — wealth advisors and P&C / life / group insurance brokers — accessible via API and UI. License status, firm history, designations, specialty mix where available.
Built for B2B vendors selling to broker networks, recruiters / aggregators consolidating broker books, carriers and wholesalers monitoring distribution. Complements RepReach — this is data about brokers; RepReach is the play to activate them.
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Untitled
Shovels for Canada
Concept · Unnamed
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Untitled — Dev Permits
Data · Canadian dev / build permits

Problems it solves

  • Canadian dev and build permit data is scattered across hundreds of municipal portals, each with its own format
  • Near-impossible to monitor permit activity nationally without a manual scraper farm
  • Construction sales, materials suppliers, and signal operators have no reliable feed of "shovels going in the ground"

How it works

  • Aggregated, normalized permit feed — accessible via API and UI as a signal source for outbound, ABM, and territory planning. Canadian-first.
Open questions: name (PermitFeed? GroundBreak?), pilot vertical (residential vs commercial vs trades), pricing model.
04
Services · What we deliver

Productized Services

Service-shaped, but with a productized spine. Each one codifies hard-won operator experience into a repeatable engagement that doesn't reinvent the wheel for every client. The hybrid tier — part product, part service.

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Custovery
Closed-loop call intelligence
In Design
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Custovery
Productized service · powered by Kernel

Problems it solves

  • Call recordings sit in Gong / Granola / Fireflies and never feed back into anything systematic
  • Insights from customer calls don't reach hiring, training, sales enablement, or product — the loop is open
  • Manual VoC review doesn't scale — patterns get lost in volume

How it works

  • Built on Kernel. Ingests calls and surrounding context, extracts patterns, and pipes a self-healing feedback loop into whichever system needs it — recruiting, sales training, product insights, retention.
Built for ops leaders, talent ops, sales enablement, product teams who need a feedback engine on top of their call data.
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RepReach
Sell the seller, codified
In Design
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RepReach
Productized service · partner-led distribution

Problems it solves

  • Partner-led distribution depends on reaching the reps inside the partner network — brokers, agents, marketplace sellers — not their head office
  • Companies pursue partner-led GTM top-down and waste cycles on logos that sign deals but never activate their reps
  • No off-the-shelf playbook for sell-the-seller — the motion is tribal knowledge sitting with a few operators

How it works

  • Codification of Shy + Shubh's experience reaching reps that drive partner-led distribution — financial-services brokers, real-estate agents, ADP marketplace sellers, and others. Repeatable engagement shape.
Built for companies pursuing partner-led / channel distribution who need to activate the reps, not just sign the partner.
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Founder Brain
The founder, made portable
In Design
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Founder Brain
Productized service · powered by Kernel + Custovery

Problems it solves

  • Founders carry the sales motion, frameworks, decision logic, and brand POV in their head — when they're not in the room, the team operates on a degraded copy
  • The personal context that compounds founder leverage — emails, texts, LinkedIn DMs, voice notes, call recordings — is fragmented across tools nobody has ever stitched together
  • Every new AI tool the founder adopts rediscovers the same context from scratch, and the founder ends up retyping their POV into prompts forever

How it works

  • Layer 1 — Portable corpus. Ingest the founder's personal sources (calls, comms, frameworks, writing, personal LinkedIn). Distill into a portable, self-updating Anchor Context the founder owns.
  • Layer 2 — Custom ACDs + integration. Layer purpose-built ACDs on top (sales coaching, brand voice, decision rationale) and wire into the founder's AI tool of choice — ChatGPT, Claude, Clay, an agent stack, whatever they actually use.
Built for founders whose voice / POV / coaching IP is the company's distinct asset — and the bottleneck on its leverage. Design partner: Adam Hoffman, Pinnacle Wealth.
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Company Brain
The company, made portable
In Design
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Company Brain
Productized service · powered by Kernel + Custovery

Problems it solves

  • Company knowledge lives across Slack, Gong, Granola, Drive, Notion — never assembled, always rebuilt per project, and decays the moment people move
  • Onboarding new hires and new AI tools repeatedly re-discovers the same context — every team pays the "explain the company" tax every quarter
  • Cross-functional decisions repeat because the rationale isn't anywhere queryable — institutional memory dies with the people who held it

How it works

  • Layer 1 — Portable corpus. Ingest the team's working artifacts (calls, docs, decisions, playbooks). Distill into a portable, self-updating Anchor Context the company owns.
  • Layer 2 — Custom ACDs + integration. Layer role and function ACDs on top (RevOps, sales, product, support) and wire into the team's AI tools of choice.
Built for scaling teams who feel the cost of re-explaining the company every project, and want institutional knowledge to outlive the people who held it. Same underlying brain as Founder Brain — wider source net, role-cut ACDs on top.