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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.

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From form fill to follow-up draft in about 90 seconds An illustrative drawing of one inbound lead travelling along a single hand-drawn thread through five stations: form fill, enrich, score, route and follow-up. The lead has passed the form, the enrichment magnifier and the scoring dial and is about to be routed to the right rep. The note in the margin says it takes about 90 seconds and nobody touched it. Form fill demo request Enrich Clay, Apollo, open web Score fit and intent Route right rep, with brief Follow-up drafted for rep approval about 90 seconds nobody touched it ILLUSTRATIVE

One lead, from form fill to follow-up draft in about 90 seconds. Illustrative.

7+
Years in B2B SaaS ops
40+
GTM platforms mastered
$1B+
Pipeline tracked and attributed
3
Engagement models

Works inHubSpot, Salesforce, Marketo, Clay, Apollo, Outreach, Gong, Looker Studio, Segment, Intercom, Pardot, Salesloft, Drift, Mixpanel, Tableau, n8n

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.

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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.

Where a go-to-market machine breaks An illustrative flow of a go-to-market machine from website to marketing automation to CRM to sales to reporting, with three numbered breaks. One: the connector between marketing automation and CRM is severed, so two reports show two different pipeline numbers. Two: all deals funnel through one founder who carries the pipeline and hits the ceiling, with no scoring or routing stations. Three: manual work such as enrichment, follow-up, report pulls and list building runs in a hand loop that eats the team. follow up by hand pull reports build lists enrich by hand 1 2 3 Your tools don't talk to each other Founder-led sales hit the ceiling Manual work is eating your team this is where it breaks everything waits on one person Website MAP marketing automation CRM Salesforce, HubSpot Reporting Sales founder-led PIPELINE NO SCORING NO ROUTING MAP REPORT CRM REPORT Two reports, two different pipeline numbers ILLUSTRATIVE

The flowWebsite, MAP (marketing automation), CRM (Salesforce, HubSpot), Sales (founder-led), Reporting. Two reports, two different pipeline numbers.

  1. 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.

  2. 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.

  3. 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 five layers of a revenue operating system, as a plant in section A botanical plate drawing of a plant in cross-section. Layer 01, data, is the roots below the soil line. Layer 02, process, is the trunk. Layer 03, automation, is the branches. Layer 04, intelligence, is the leaves and fruit. Layer 05, governance, is a trellis arch around the whole plant. A hand note says most teams buy at layer one and expect results at layer five. 05 GOVERNANCE Access, approval gates, audit trail, AI policy 04 INTELLIGENCE Attribution, scoring, forecasting, cost-per-stage 03 AUTOMATION Agents, routing, enrichment, follow-up 02 PROCESS Lifecycle, SLAs, handoffs, definitions 01 DATA Object model, taxonomy, hygiene, integration most teams buy at layer one and expect results at layer five SOIL LINE FIG. 1 THE FIVE LAYERS OF A REVENUE OPERATING SYSTEM, IN SECTION

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.

  1. 05
    Governance

    Access, approval gates, audit trail, AI policy.

    Without itAgents run unsupervised, legal gets involved, projects get frozen.

  2. 04
    Intelligence

    Attribution, scoring, forecasting, cost-per-stage.

    Without itDecisions get made on the loudest opinion in the room.

  3. 03
    Automation

    Agents, routing, enrichment, follow-up.

    Without itYour best people do work a workflow should do.

  4. 02
    Process

    Lifecycle, SLAs, handoffs, definitions.

    Without itEvery team measures the funnel differently.

  5. 01
    Data

    Object model, taxonomy, hygiene, integration.

    Without itNothing 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.

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.

GTM Stack Architecture

We assess, redesign, and implement your connected revenue stack, MAP to CRM to analytics, so every tool talks to every other tool and every dollar is attributable.

  • Full stack audit and gap analysis
  • CRM and MAP integration design
  • Data model and taxonomy alignment
  • Tool consolidation and migration planning
  • Attribution and tracking architecture

Revenue stack mapWebsite forms (forms and UTM tags), MAP (Marketo or HubSpot), CRM (Salesforce), Data layer (Segment), Analytics (Looker Studio). Two seams stitched: attribution and tracking architecture.

Learn more
Revenue stack map with two seams being stitched A hand-drawn map of a revenue stack inside an arch: website forms feed a marketing automation platform (Marketo or HubSpot), then Salesforce CRM, a Segment data layer, and Looker Studio analytics, joined by pipes carrying one gold thread. Two seams in the pipes are being repaired with stitches and a needle, labelled attribution and tracking architecture, with a close-up of one seam in an embroidery hoop. Illustrative. Website forms FORMS AND UTM TAGS MAP MARKETO OR HUBSPOT CRM SALESFORCE Data layer SEGMENT Analytics LOOKER STUDIO attribution and tracking architecture A SEAM, CLOSE UP ILLUSTRATIVE

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
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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

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.

Total elapsed time: about 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
AI agent workflow with a human approval gate A left-to-right flowchart drawn as one gold running-stitch thread. A lead enters, the agent researches and enriches it from Clay, Apollo and the open web, then scores it for fit and intent. The thread forks into three outcomes: hot leads skip the line, nurture leads are kept warm, and disqualified leads are not dumped on sales. Hot leads are routed instantly and get a personalized follow-up drafted from the research. Then an arch-shaped human approval gate with a check: queued for rep approval or sent on rules. The result is written back to the CRM. A strip underneath shows an audit log and a kill switch. Illustrative. AGENT STEP HUMAN DECISION ILLUSTRATIVE product signup Form fill, demo request, Lead enters 01 02 Research and enrichment Firmographics, tech stack, funding, hiring signals FROM CLAY, APOLLO, OPEN WEB against your model Fit and intent qualification Scoring and 03 or named-account Round-robin, territory Instant routing 05 06 Personalized follow-up Drafted from the research 08 Write back to CRM Record and activity updated Queued for rep approval or sent on rules Human approval gate 07 04 HOT skips the line NURTURE kept warm for later DISQUALIFIED not dumped on sales agent works, human decides least-privilege access AUDIT LOG every step is recorded KILL SWITCH stop the agent at once

  1. 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.

  2. Research and enrichment

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

  3. Scoring and qualification

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

  4. Instant routing

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

  5. 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.

Three outcomes
  • Hot skips the line
  • Nurture kept warm for later
  • Disqualified not dumped on sales
Agent works, human decides
  • Human approval gate Queued for rep approval or sent on rules
  • Write back to CRM Record and activity updated
  • Audit log Every step is recorded
  • Kill switch Stop the agent at once
  • Least-privilege access

The Opsmarshal Terminal

We do not just describe the control plane. We run one in public. The Terminal is an evidence-first map of the martech market, maintained by the same governed agents we build for clients. Every data point links to its source. A missing number means no qualifying evidence stored, not a verdict on the vendor.

15,505Product universe
49Core categories
921Platforms tracked
5Gates per agent action
Browse the landscape →Open the live Terminal
Screenshot of the live Opsmarshal Terminal: the martech market overview with product universe, categories and platforms tracked Screenshot of the live Opsmarshal Terminal: the martech market overview with product universe, categories and platforms tracked
A real capture of the live Terminal, not an illustration.

From diagnostic to deployed in 90 days

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

What happens in the first 90 days?

A typical 90-day engagement as a week-by-week Gantt chart A Gantt chart with a twelve-week axis. Diagnose runs weeks 1 to 2 and ends with a written ops assessment. Architect runs weeks 2 to 3 and ends with a signed-off target-state architecture. Deploy, the big build, runs weeks 3 to 10 and ends with integrations wired, agents deployed and dashboards live, with a sprig growing from its end. Iterate is a dashed bar that begins at week 10 and fades off the right edge as ongoing work. Illustrative: the timeline is typical, not a promise. ILLUSTRATIVE TYPICAL TIMELINE, NOT A PROMISE WEEK 1 2 3 4 5 6 7 8 9 10 11 12 Diagnose Map how revenue ops runs today Architect Design the target-state stack Deploy Integrations, agents, dashboards Iterate Retainer clients, ongoing END OF WEEK 2 Written ops assessment END OF WEEK 3 Target-state architecture signed off WEEK 10 Integrations wired, agents deployed, dashboards live WEEKS 1 TO 2 WEEKS 2 TO 3 WEEKS 3 TO 10 the big build FROM WEEK 10 keeps going
  1. Weeks 1-2

    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.

    End of week 2Written ops assessment

  2. Weeks 2-3

    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.

    End of week 3Target-state architecture signed off

  3. Weeks 3-10

    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.

    Week 10Integrations wired, agents deployed, dashboards live

  4. Ongoing

    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.

    From week 10Retainer clients, ongoing

Typical timeline, not a promise.

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.

How fast does a new lead reach a rep? Before and after chart. Before, a new lead waited 4 hours to reach a rep, drawn as a tall hatched bar of four one-hour blocks. After, it takes 90 seconds, drawn as a tiny gold sun sitting on the ground line. Tagged as a representative outcome. How fast does a new lead reach a rep? 4hrs 1 BLOCK = 1 HOUR 90sec lead is cooling a rep is already on it BEFORE AFTER REPRESENTATIVE OUTCOME

Series B SaaS · 140 employees

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.

How much pipeline can marketing actually attribute? Before and after chart drawn as two arches filled like vessels. Before, marketing could attribute about 40 percent of pipeline, so the first arch is filled to about two fifths. After, it is 95 percent, so the second arch is nearly full. Tagged as a representative outcome. How much pipeline can marketing actually attribute? 40% about 95% the rest is guesswork traced to a real source BEFORE AFTER REPRESENTATIVE OUTCOME

Series A SaaS · PLG motion

Attribution coverage

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

How many SDR hours go to manual enrichment? Before and after chart drawn as two hourglasses. Before, the glass is full of gold sand and manual enrichment takes 10 hours per week. After, the glass is empty and it takes 0 hours per week. Tagged as a representative outcome. How many SDR hours go to manual enrichment? BEFORE 10hrs PER WEEK copy, paste, repeat AFTER 0hrs PER WEEK it runs on its own REPRESENTATIVE OUTCOME

Growth-stage · 60-rep sales org

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.

How long does the board report take? Before and after chart drawn as calendar cells. Before, the board report took 3 weeks, drawn as three rows of working days with the weekends dashed. After, it takes the same day, drawn as a single finished cell at the same scale. Tagged as a representative outcome. How long does the board report take? BEFORE AFTER 3weeks same day chasing exports board day ready when the board asks REPRESENTATIVE OUTCOME

Series C · Multi-product

Board reporting cycle

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

How many cold emails get a reply? Before and after chart drawn as two strips of 100 small envelopes. Before, 1.2 percent of cold emails get a reply, so about one envelope is filled gold. After, 4.8 percent do, so almost five are filled. Tagged as a representative outcome. How many cold emails get a reply? BEFORE, 100 COLD EMAILS AFTER, 100 COLD EMAILS 1.2% 4.8% = A REPLY REPRESENTATIVE OUTCOME

Series B · Outbound-led

Cold email reply rate

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

How long does a stalled CRM migration take to ship? Before and after chart drawn as two roads. Before, a stalled CRM migration sat in a 6 month backlog, drawn as a long road blocked by a barrier that fades to a dotted line. After, it ships in 90 days, drawn as a road half as long that reaches an arch with a sun beyond it. Tagged as a representative outcome. How long does a stalled CRM migration take to ship? BEFORE 6 month backlog AFTER 90 days stalled shipped REPRESENTATIVE OUTCOME

Post-migration · HubSpot → SFDC

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.

Read the full case studies →
Illustrated portrait of Ananda Narasimhan, founder of Opsmarshal Illustrated portrait of Ananda Narasimhan, founder of Opsmarshal
Illustrated portrait of Ananda Narasimhan, founder of 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.

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
More about us

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?

Diagnostic: $2,500, credited toward any build. Targeted Build: from $15,000. Revenue Operating System Build, the 90-day, all-five-layer engagement: from $40,000. Fractional RevOps: from $5,000/month. Scope, number of systems connected, migration work, and agents taken to production move the number within a tier. 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.

Book a callSee services
The thread arrives at an open doorway A single hand-drawn thread with round nodes wanders in from the left and ends at the doorstep of an open arched doorway. A gold sun rests on the horizon beyond the doorway, light spills onto the ground, and a leafy sprig stands at each side. A hand note reads 30 minutes. No pitch deck. 30 minutes. No pitch deck.