AI for RevOps

A CRM that updates itself.

We engineer the autonomous layer under your revenue stack - enrichment, hygiene, routing, scoring, and forecasting that run without a single manual touch, so reps sell instead of maintaining a CRM.

Get your Revenue Operations blueprint ↳ 30-min audit · zero obligation

The outcome

3.5x

more pipeline touched per rep, with zero added headcount

↳ The Revenue Intelligence Engine

[ 000 ]Trusted by operators

[ 01 ]The status quo

What this costs you today.

Most RevOps teams are the human glue between HubSpot, Salesforce, Clay, and a graveyard of half-documented automations. The work that should be your leverage - clean data, fast routing, accurate forecasts - is exactly the work that eats your week.

Lead routing, scoring, and CRM hygiene live in disconnected workflow tools that break silently and route deals to the wrong rep.

Forecasts are spreadsheet archaeology - reps sandbag, fields go stale, and the number you present to the board is a guess dressed as a model.

Every new automation is owned by whoever built it, so when it breaks at quarter-end nobody knows the logic and nobody can fix it.

Horizontal AI 'copilots' bolt onto your CRM but can't see across marketing, sales, and CS - so the agents act blind and you lose the audit trail.

[ 02 ]What we build for Revenue Operations

The systems, named and shipped.

RevOps is where agents either compound or quietly corrupt the database. The win isn't more bots - it's a governed layer your team owns, where every agent's logic, inputs, and kill switch live in one place. We build the control plane first, then the agents that run on it.

★ Flagship · built for Revenue Operations

AI-Orchestration Control Plane

A governed layer RevOps owns that monitors every agent and automation across marketing, sales, and CS - one place to see what each one did, why, and on what data. Logic lives in version control you can read, every action writes to an audit trail, and every agent has a kill switch. Ships into your repo and runs on your infra, so the orchestration that runs your revenue is never a black box you rent.

GTM / Sales

CRM Hygiene Agent

Continuously dedupes, normalizes, and enriches records against Clay and Apollo - fixing titles, owners, account hierarchies, and stale fields before they poison routing, scoring, and reporting.

Dynamic Lead-Routing Engine

Routes every inbound and signal-sourced lead in real time on rules you can read and change - territory, segment, capacity, round-robin, named-account ownership - with a logged reason for every assignment.

Adaptive Lead-Scoring Model

A scoring model that learns from closed-won and closed-lost instead of a static point system, reweights as your ICP shifts, and exposes why each lead scored what it did so reps actually trust it.

Signal-to-Sequence Orchestrator

Watches intent and engagement signals from 6sense, Common Room, and product usage, then triggers the right sequence, task, or alert the moment an account heats up - no SDR manually refreshing a dashboard.

Content / Marketing

Attribution & Pipeline-Source Reporting Agent

Stitches touchpoints across ad platforms, campaigns, and CRM into a defensible source-of-pipeline view, so marketing and sales argue from one number instead of two dashboards.

Campaign-to-CRM Feedback Loop

Pushes downstream deal outcomes back to the campaigns that sourced them, so spend follows what actually converts to pipeline and revenue - not what generated the most MQLs.

Internal Ops

Revenue-Intelligence Brain

A RAG brain over Gong calls, CRM history, and deal notes that answers 'what's really going on in this deal / this segment / this quarter' in plain language, with citations back to the call and the record.

Forecasting Agent

Builds a bottoms-up forecast from deal signals, rep behavior, and historical conversion - flagging sandbagged and at-risk deals - so your committed number is grounded in evidence, not vibes.

Data-Governance & Field-Definition Guardian

Enforces field definitions, required-data rules, and naming conventions across the stack, and alerts when a workflow or human starts drifting - keeping the data layer trustworthy enough for the agents above to run on.

[ 03 ]How we build it

Engineered, owned, operated.

Step 01

Map your workflow

We trace how your team actually works - the inputs, the decisions, the systems - before writing a line. The system of work is the moat, and we engineer it deliberately, not generically.

Step 02

Build & ship to your repo

We build the agents and the grounded data layer, wire them into your tools, and ship the code into your repository - not a no-code platform you can never leave.

Step 03

Ground, guardrail, review

Every system answers from your verified data, is gated by guardrails and human review on the decisions that matter, and is backed by evals before you trust it in production.

Step 04

Host, operate, evolve

We deploy on real infrastructure (Railway, Vercel, Cloudflare), operate it in production, and tune it every month as the models move. Built once, yours forever.

[ 04 ]By the numbers

15-25 hrs/wk

Manual data work reclaimed per RevOps team (2026 industry range)

30-50%

Less manual data entry and CRM cleanup reported by AI-augmented RevOps teams

15-25%

Forecast-accuracy improvement reported in the first quarters of adoption

↳ Industry benchmarks, not Anfloy client metrics - we report your real numbers once you're live.

[ 05 ]The offer

The Revenue Intelligence Engine

A self-maintaining revenue engine: every lead enriched, every record clean, every deal routed and scored - wired into your CRM, governed by you, and live in weeks.

Get your Revenue Operations blueprint

+Signal-based enrichment + ICP-fit lead scoring

+Always-on CRM hygiene, dedupe, and field normalization

+Dynamic routing + handoff with a context summary attached

+Forecast, pipeline-risk, and revenue-leak reporting on a cadence

+A governance layer you own - logic, inputs, and audit trail visible

[ 06 ]Why Anfloy

Versus what you'd do instead.

· What matters

· In-house or off-the-shelf

· Anfloy

Time to value

Months to hire + ramp a team, or a SaaS tool that stops at 60%

Shipped in weeks - the full system, not a fraction

The AI

Generic and identical for every customer

Engineered to your workflow, your data, your edge

Ownership

Rented - it lives in their UI, on their terms

In your repo. Built once, yours forever

Where it runs

Their cloud, or your infra as your problem to run

Your infra - deployed and operated by us

Maintenance

Another full-time hire, or you wait on their roadmap

We tune it monthly as the frontier moves

Cost shape

Salaries, or a per-seat tax that scales with usage

A fixed build - an asset on your books, not a tax

Time to value

In-house / off-the-shelfMonths to hire + ramp a team, or a SaaS tool that stops at 60%

AnfloyShipped in weeks - the full system, not a fraction

The AI

In-house / off-the-shelfGeneric and identical for every customer

AnfloyEngineered to your workflow, your data, your edge

Ownership

In-house / off-the-shelfRented - it lives in their UI, on their terms

AnfloyIn your repo. Built once, yours forever

Where it runs

In-house / off-the-shelfTheir cloud, or your infra as your problem to run

AnfloyYour infra - deployed and operated by us

Maintenance

In-house / off-the-shelfAnother full-time hire, or you wait on their roadmap

AnfloyWe tune it monthly as the frontier moves

Cost shape

In-house / off-the-shelfSalaries, or a per-seat tax that scales with usage

AnfloyA fixed build - an asset on your books, not a tax

[ 07 ]Where it plugs in

Wired into your stack.

HubSpotSalesforceAttioClayApollo6senseGongCommon RoomSnowflakeSlack

[ 08 ]Questions

The honest answers.

Q01

Do we own the control plane and the agents, or are we renting them?

You own all of it. We build into your repository and hand over the full source, the agent logic, and the documentation. There's no Anfloy platform you log into and no per-seat license on the thing that runs your revenue. If you parted ways with us tomorrow, your engineers could read, run, and extend every agent - that's the whole point of a layer RevOps controls.

Q02

What happens when an agent breaks at quarter-end?

Every agent has a kill switch and writes to an audit trail, so the first thing you can do is stop it cleanly without taking down the rest of the stack. Because the logic lives in version-controlled code you can read - not a no-code canvas only one person understands - the failure is diagnosable rather than mysterious. We also build alerting so you hear about a drift or failure before a rep does, and we're on call during the stabilization window after launch.

Q03

How long until something is live?

We scope a first agent - usually CRM hygiene or lead routing, where the pain is sharpest - to ship in a few weeks, not a few quarters. The control plane gets stood up alongside it so the very first agent is governed from day one. From there we add agents incrementally, each one live and earning its keep before we start the next, so you're never waiting on a big-bang launch.

Q04

Does this run on our infrastructure or yours?

Yours. We deploy on real infrastructure you control - typically Railway, Vercel, or Cloudflare - connected to your own CRM, warehouse, and tool credentials. Your customer and revenue data never lives in a black-box SaaS you can't audit. You hold the keys, the hosting account, and the data, and we configure it to your security and compliance requirements.

Q05

We already pay for HubSpot/Salesforce AI features. Why build custom?

Native CRM copilots are good at acting inside their own four walls and blind to everything outside them. They can't reconcile a Gong signal against a Clay enrichment against a product-usage spike, and they don't give RevOps a single governed place to see and stop every automation. We build the layer that sits across your whole stack - orchestrating the native tools rather than competing with them - so you get cross-system intelligence and ownership the platform vendors will never sell you.

Q06

Will agents make a mess of our CRM data?

The opposite - cleaning and protecting the data layer is the first thing we build. The hygiene agent and field-definition guardian enforce your rules so every other agent runs on trustworthy records, and every write is logged and reversible. We start in a staging or dry-run mode so you can watch what an agent would do before it touches production. Governance isn't a feature we add later; it's the foundation everything else stands on.

[ 09 ]Other industries we build for

Growth-Stage TechGrowth-Stage TechWe engineer the AI layer around your product - support, onboarding, and renewal signals running in the background so your team stays on the roadmap, not in the queue.AgenciesAgenciesWe automate the parts of agency life nobody wants to do - reporting, content ops, and client comms - so your team ships work and proves ROI, not busywork.Info Businesses & CoachingInfo Businesses & CoachingWe engineer the engine behind your offer - applicant screening, student support, and a coach grounded in your own methodology - so you enroll the right people and deliver the outcome at scale, without becoming the bottleneck.

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