RevOps × AI Agentic Workflows

We Build the Machine.
You Run the Company.

We design and deploy the revenue operating system underneath B2B GTM teams. The data layer, the process layer, the intelligence layer, and the AI agents that run on top of them. Built in 90 days, owned by you.

7+
Years in B2B SaaS ops
40+
GTM platforms mastered
$1B+
Pipeline tracked & attributed
Works in
HubSpot Salesforce Marketo Clay Apollo Outreach Gong Looker Studio Segment Intercom Pardot Salesloft Drift Mixpanel Tableau n8n HubSpot Salesforce Marketo Clay Apollo Outreach Gong Looker Studio Segment Intercom Pardot Salesloft Drift Mixpanel Tableau n8n

Why Teams Call Us

Nobody hires ops consultants on a quiet Tuesday

Every engagement starts with an event. Here are the ones that bring people to this page. If one of these is your quarter, the first call is worth thirty minutes.

New CRO or CMO

"I inherited a stack I can't audit and a forecast I can't defend."

Where we startA two-week written diagnostic before you commit to a rebuild.

Round just closed

"We have budget and 18 months. The ops debt will eat both."

Where we startTarget-state architecture ahead of the hiring wave.

CRM migration in flight

"It stalled. Everyone's afraid of the data."

Where we startUnblock, dedupe, ship inside the quarter.

Pipeline flattened

"Volume is fine. Conversion isn't. Nobody can tell me why."

Where we startFunnel diagnostic against the actual data, not the dashboard.

AI pilot didn't land

"We ran the pilot. Nothing showed up in revenue."

Where we startReadiness and governance review, then rebuild the measurement.

Three teams, three numbers

"Marketing, sales and finance report different pipeline."

Where we startOne data model, one definition set, one source.

Headcount scaling fast

"Every new rep makes the process problem worse."

Where we startRouting, SLA and lifecycle before the next cohort starts.

CAC moving the wrong way

"The board wants efficiency and I can only show spend."

Where we startCost-per-stage instrumentation and stack consolidation.

Post-merger or multi-entity

"Two CRMs, two taxonomies, one board deck."

Where we startEntity model design and consolidation sequencing.

The Reality

The GTM machine breaks in three places

These show up in the boardroom as three different problems: CAC drifting up, a forecast nobody trusts, and an AI investment with no revenue line attached to it. They are the same problem wearing three coats.

01

Your tools don't talk to each other

The MAP doesn't sync cleanly to the CRM. Attribution is guesswork. Sales and marketing are reporting different numbers to the same leadership team. Nobody trusts the data.

02

Founder-led sales hit the ceiling

The pipeline runs on relationships and heroics. There's no repeatable system behind it — no lead scoring, no routing logic, no predictable forecast. You're scaling a person, not a process.

03

Manual work is eating your team

Enrichment, follow-up, report pulls, list building — your best people are doing work that should be automated. Every hour spent on this is an hour not spent on strategy, pipeline, and growth.

The Model

A revenue operating system has five layers

Most companies buy tools at layer one and expect outcomes at layer five. That gap is the entire consulting market. Here is the stack we build, bottom up, and what breaks when a layer is missing.

05
Governance
Access, approval gates, audit trail, AI policy.
Agents run unsupervised, legal gets involved, projects get frozen.
04
Intelligence
Attribution, scoring, forecasting, cost-per-stage.
Decisions get made on the loudest opinion in the room.
03
Automation
Agents, routing, enrichment, follow-up.
Your best people do work a workflow should do.
02
Process
Lifecycle, SLAs, handoffs, definitions.
Every team measures the funnel differently.
01
Data
Object model, taxonomy, hygiene, integration.
Nothing above this layer is trustworthy.

AI lives at layer three. It only produces revenue if layers one and two are real and layer four can measure it. That is why most AI pilots produce demos instead of pipeline.

What We Do

Four ways we build the machine

Each service solves a distinct layer of the revenue problem. Most clients start with GTM Stack Architecture, then layer in the rest.

02 / 04

Marketing Operations

Email programs, campaign infrastructure, lead lifecycle, and deliverability — built to run reliably and scale without breaking.

  • Email deliverability and domain health
  • Campaign operations and UTM governance
  • Lead lifecycle and nurture design
  • MAP setup, migration, and audits
  • Form, landing page, and web ops
Learn more
03 / 04

Revenue Operations

Pipeline visibility, lead routing, CRM hygiene, and forecasting — aligned across sales and marketing so leadership gets one version of the truth.

  • Lead scoring and routing logic
  • CRM architecture and data hygiene
  • Pipeline reporting and forecasting
  • Sales and marketing SLA design
  • Multi-touch attribution modeling
Learn more
04 / 04

AI Enablement & Agentic Workflows

Most AI GTM projects fail for the same reason: the pilot proves the model works and nobody built the layer that makes it measurable. We work in three tracks, and we will tell you honestly which one you need.

  • Track A. Readiness and governance. Where AI fits, access scoping, approval gates, a written AI policy
  • Track B. Agent deployment. Enrichment, research, personalisation, routing, reporting, follow-up
  • Track C. Measurement. Baseline, cost per agent action, hours displaced, revenue attribution
  • Built inside your stack on n8n, Make, or custom LLM plus CRM integrations
  • Least-privilege access, documented and handed over
Learn more

Watch the Machine Work

One lead. Zero human touches.

This is what an Opsmarshal agentic workflow does the moment a lead hits your funnel — while your team is in a meeting, or asleep.

00 · Trigger

Lead enters the funnel

Form fill, demo request, or product signup. The agent picks it up in under a second — no queue, no SDR triage.

01 · Enrich

Research & enrichment

Firmographics, tech stack, funding, hiring signals, ICP match — pulled from Clay, Apollo, and the open web, written back to the CRM.

02 · Score

Scoring & qualification

Fit and intent scored against your model. Disqualified leads get nurtured, not dumped on sales. Hot leads skip the line.

03 · Route

Instant routing

Round-robin, territory, or named-account logic. The right rep gets the lead with full context — research brief included.

04 · Engage

Personalized follow-up

A first-touch email drafted from the research — referencing their stack, their hiring, their actual problem. Queued for rep approval or sent on rules.

opsmarshal-agent · live

Total elapsed time: ~90 seconds. The same workflow done manually takes a rep 30–45 minutes — per lead. We build these on n8n, Make, or custom LLM + CRM integrations, fitted to your stack.

See AI Agent services →

How We Work

From diagnostic to deployed — in 90 days

A focused sprint model. No 6-month discovery phases. No committee-driven delays.

Week 1–2
01

Diagnose

We audit your full GTM stack — data flows, tool integrations, process gaps, and team workflows. You get a written ops assessment with prioritized findings.

Week 2–3
02

Architect

We design the target-state architecture — data model, integration map, automation flows, and reporting layer. Every decision is documented and aligned with your team.

Week 3–10
03

Deploy

We build and implement — clean, documented, tested. Integrations wired up. Workflows running. Agents deployed. Dashboards live. You can see the output before we wrap.

Ongoing
04

Iterate

Retainer clients get ongoing ops management, monthly system reviews, and continuous improvement as your stack and team evolve. Most things compound over 90 days.

Before / After

What the machine looks like when it works

Representative outcomes from the kinds of engagements we run. Different stack, same physics: clean data in, automated motion out.

Series B SaaS · 140 employees
4 hrs 90 sec

Speed-to-lead

Agentic routing replaced manual triage. Every inbound lead enriched, scored, and in a rep's queue with a research brief — before the prospect closes the tab.

Series A SaaS · PLG motion
~40% 95%

Attribution coverage

Rebuilt UTM governance, conversion paths, and the MAP→CRM sync. Marketing finally reports the same pipeline number as finance.

Growth-stage · 60-rep sales org
10 hrs/wk 0

Manual enrichment time

An enrichment agent on Clay + CRM APIs took list building and account research off the SDR team entirely. Headcount redeployed to actual selling.

Series C · Multi-product
3 weeks Same day

Board reporting cycle

Pipeline, conversion, and attribution dashboards rebuilt on one data model. The deck that took an analyst three weeks now refreshes itself.

Series B · Outbound-led
1.2% 4.8%

Cold email reply rate

Deliverability rebuilt from the domain up, plus AI personalization drawing on real account research instead of {{first_name}} templates.

Post-migration · HubSpot → SFDC
6 mo backlog 90 days

Migration & cleanup

A stalled CRM migration unblocked, deduped, and shipped inside one quarter — with lifecycle stages and routing live on day one of cutover.

// Representative engagement outcomes. Specifics vary by stack, data quality, and team. We'll tell you what's realistic on the first call.

About Opsmarshal

Built by someone who's lived in the stack

Opsmarshal was founded by Ananda Narasimhan after 7+ years embedded in the ops layer of B2B SaaS companies — running email systems, building lead scoring models, architecting attribution, and sleeping next to dashboards.

We're not a generalist agency that added "RevOps" to the services page. This is the only thing we do.

HubSpot Salesforce Marketo Lead Scoring Attribution PLG Motion AI Workflows Data Layer

Leave me in a room with a laptop, an internet connection, and access to your GTM stack. I'll come back with a map of everything that's broken — and a plan to fix it.

Ananda Narasimhan
Founder & Principal, Opsmarshal
7+
Years in B2B SaaS ops
40+
GTM platforms mastered
$1B+
Pipeline tracked
3
Engagement models

Straight Answers

Questions we get on every first call

If yours isn't here, ask it on the call — you'll get the same kind of answer.

How are you different from hiring a RevOps person in-house?+

A senior RevOps hire runs $140–180K plus 3–6 months of ramp — and one person rarely covers MAP administration, CRM architecture, attribution, and AI automation. We bring all four from day one, on a 90-day sprint. Many clients use us to build the machine, then hire one person to run it. We'll even help you write the job description.

We're mid-migration / our CRM is a mess. Is it too early to engage?+

That's the best time. Cleaning up mid-flight is dramatically cheaper than re-platforming a year of bad data later. Stalled migrations and messy CRMs are the most common starting state we see — the Diagnose phase exists exactly for this.

What does an engagement cost?+

It depends on scope, but the shape is always one of three models: a fixed-scope project (the 90-day build), a monthly retainer (ongoing ops management), or a fractional ops-lead arrangement. You'll get a concrete number after the diagnostic call — not a "it depends" dance. No surprise invoices.

Are the AI agents safe to run on our customer data?+

Agents run inside your stack with scoped, least-privilege API access — we don't pipe your CRM through third-party black boxes. Every agent has human-approval gates where it matters (like outbound sends), full audit logs, and a kill switch. You own the infrastructure; we build and document it.

We already have an agency / a marketing team. Where do you fit?+

We're the layer under them. Demand gen agencies create campaigns; we build the infrastructure those campaigns run on — routing, scoring, attribution, deliverability. Most agencies are happy we exist, because their results finally become measurable.

What happens after the 90-day sprint ends?+

Everything we build is documented and handed over — architecture docs, runbooks, loom walkthroughs. From there, teams either run it themselves, keep us on a light retainer for monthly reviews, or expand into the next layer (most commonly AI agents after the stack rebuild). No lock-in by design.

Which stacks do you actually work in?+

Deepest: HubSpot, Salesforce, Marketo, and Pardot on the platform side; Clay, Apollo, Outreach, and Salesloft on the outbound side; n8n, Make, and custom LLM + API builds for automation. 40+ GTM tools total. If your stack has something exotic, we'll tell you on the first call whether we've run it before.

How do we start?+

A 30-minute strategy call. You walk us through your stack and your bottleneck; we tell you honestly whether and how we'd fix it — including the cases where you don't need us. If it's a fit, the written diagnostic starts the following week.

Ready to build the machine?

30-minute strategy call. No pitch deck. Just an honest look at your stack and what it would take to fix it.