What we fix - Every startup breaks in the same places.
Sales & Revenue
Your pipeline is leaking. Leads come in but nobody follows up fast enough, the CRM is a mess, and outbound is manual and inconsistent. We build the system that handles it end to end, so nothing falls through.
Capabilities: CRM automation, Lead scoring, Outbound sequencing, Pipeline analytics, Follow-up systems.
Growth & Marketing
Posts by hand. Outreach one at a time. Campaigns from a spreadsheet. We build the system that runs it on autopilot, tests what works, and gets smarter as you go.
Capabilities: Content repurposing, Campaign automation, Lead generation, SEO workflows, Social automation.
Customer Experience
New users don’t know where to start and support tickets get lost in a shared inbox nobody owns. We build onboarding flows, support automation, and feedback loops that make customers stick around.
Capabilities: Onboarding automation, Support triage, Customer health tracking, Feedback systems, Knowledge bases.
Internal Operations
Hiring is a spreadsheet. Invoices are manual. Reporting is someone’s Friday afternoon. We set up the internal systems that let a small team run like a much bigger one.
Capabilities: HR automation, Invoice processing, Reporting dashboards, Document workflows, Team knowledge bases.
Three steps. That's it. From fire to fixed.
Step 01: Diagnose - Find the real problem
We look at your current tools, how your team works, and where things are getting stuck. Sometimes it’s a big structural issue. Sometimes it’s a small fix that saves hours. Either way, we figure it out together.
Includes: Workflow audit, Tool stack review, Team interviews, Bottleneck mapping, Priority mapping.
Step 02: Build - Build it. Test it. Ship it.
We build automations, integrations, and AI agents on your actual stack with your actual data. You see working prototypes in days, not months. Nothing ships until your team has tested it.
Includes: Rapid prototyping, Real data testing, AI agent development, Integration setup.
Step 03: Optimize - Make it stick
We don’t hand it off and disappear. We monitor what’s working, fix what isn’t, and adapt the system as your team grows. The goal is a system that runs without us, not one that depends on us.
Includes: Performance monitoring, System updates, Scaling systems, New automation builds, Team training.
See it in action - We've built these before. We'll build them for you.
View all case studies
End-to-End Outreach System - 45% Less Time on Prospecting
Industry: B2B SaaS. Category: Sales & Revenue. Timeline: 2 weeks.
You give it your ICP. It finds leads, enriches them, writes personalized emails and LinkedIn messages, and runs the sequences. You get a working pipeline and data on which profiles actually reply.
We wired up a system that finds leads matching the ICP, layers on firmographic and intent data, writes personalized outreach for email and LinkedIn, and tracks what gets replies so targeting improves on its own.
Challenge: The founders were doing all outbound by hand. Researching prospects, writing emails one at a time, tracking replies in spreadsheets. Pipeline was thin and follow-ups kept slipping.
Solution
- Defined ICP criteria and set up automated lead sourcing from Sales Navigator into Clay.
- Ran every lead through Clay's waterfall enrichment for firmographic data, tech stack, and recent company activity.
- Plugged in Apollo.io for verified contact info and deliverability scoring.
- Set up an AI pipeline that writes personalized email and LinkedIn sequences based on each lead's context.
- Configured Instantly for email warm-up, sending rotation, and follow-ups with smart reply detection.
- Added engagement tracking so the system learns which ICP profiles convert best.
Tools Used
- Clay: Pulls firmographic data from 50+ providers and stitches together lead profiles.
- Apollo.io: Finds verified work emails and scores them for deliverability.
- Sales Navigator: Sources leads matching the ICP with advanced filters.
- Instantly: Handles email warm-up, sending rotation, and automated follow-ups.
Results
- 11% Positive Reply Rate - 11% positive replies on cold outreach. Industry average is around 3-5%.
- Full Pipeline Automated - From lead sourcing to follow-up, the whole thing runs without anyone touching it.
- Multi Channel Sequences - Email and LinkedIn outreach running together, each with its own messaging.
- ICP Insights - Analytics show which profiles convert, so targeting gets sharper over time.
Result: 11% positive reply rate, fully hands-off.
Self-Updating Help Center - 90% Faster Article Creation
Industry: SaaS. Category: Customer Experience. Timeline: 4 weeks.
Watches support conversations, spots gaps in your docs, flags articles that have gone stale, and drafts new ones when features ship.
We set up a system that reads support tickets for patterns, figures out what's missing from the docs, flags anything outdated, and writes draft articles when new features go out. Took article creation from hours to about 15 minutes.
Challenge: Support kept answering the same questions because the docs were either outdated or just didn't exist. Features shipped without documentation, and nobody had time to write it.
Solution
- Hooked up Intercom to pull support conversations and spot recurring questions using Claude.
- Built a gap analysis that compares what people are asking against what's already in the Notion help center.
- Set up auto-flagging for stale articles based on product changelog and ticket trends.
- When a new feature ships, Claude drafts a help article from release notes and recent support context.
- Drafts land in Notion with status tracking so someone can review before publishing.
Tools Used
- Make.com: Connects Intercom, Claude, and Notion with conditional logic and scheduling.
- Claude API: Reads support patterns, spots gaps, and writes article drafts.
- Intercom: Source of support conversations and recurring question data.
- Notion: Where help articles live, with status tracking and review workflows.
Results
- 15 min Per Article - Down from 2-3 hours. The AI draft just needs a human pass before publishing.
- Auto Gap Detection - Spots missing documentation by comparing support questions against existing articles.
- Stale Article Flagging - When the product changes, outdated articles get flagged before anyone has to notice.
- Ship Day Docs - Features get a documentation draft the same day they go live.
Result: Article creation went from 2-3 hours to 15 minutes.
Automated Reporting Dashboard - 4 hrs Saved Every Week
Industry: Cross-industry. Category: Internal Operations. Timeline: 1 week.
One dashboard, live data from 10+ tools. Product, finance, marketing, support — all in one place. Comes with AI-written weekly summaries.
We pulled data from 10+ tools into a single dashboard so the team stops copy-pasting numbers into slides every Monday. Added AI summaries that flag what actually changed that week.
Challenge: Leadership was making decisions on stale numbers because reporting was a manual chore. Data sat in 10+ tools and nobody had a single place to look.
Solution
- Listed every data source: Mixpanel for product, Stripe for finance, Google Analytics for marketing, plus support and HR tools.
- Piped everything into a unified data layer.
- Set up Metabase dashboards showing product usage, revenue, marketing performance, and support metrics in real time.
- Added AI weekly summaries that call out trends, anomalies, and things worth acting on.
- Wired up automated Slack delivery so leadership gets the report without asking.
Tools Used
- Mixpanel: User behavior, feature adoption, and engagement numbers.
- Stripe: Revenue, MRR, churn, and billing data, updated live.
- Google Analytics: Traffic, conversion funnels, and which channels are working.
- Metabase: Where all the dashboards live. Interactive, with drill-down.
Results
- 0 Manual Hours - Nobody spends time pulling numbers anymore. Data updates on its own.
- 10+ Tools Unified - Product, finance, marketing, and support data in one view for the first time.
- AI Weekly Insights - Short AI summaries flag what changed so you don't have to read every chart.
- Real-time Data - Decisions happen on today's numbers, not last week's.
Result: 4+ hours of weekly manual reporting gone.
Product-to-Content Engine - <24 hrs Ship to Publish
Industry: SaaS. Category: Growth & Marketing. Timeline: 3 weeks.
It watches what your product team ships, figures out what's worth talking about, writes the content, and routes it to the right channel. No one has to remember to do it.
We built a pipeline that picks up product releases, decides which ones matter, writes blog posts and social updates, and gets them out within a day. Marketing stopped being the bottleneck.
Challenge: Marketing never knew when features shipped. Updates sat for weeks with no announcement. Writing content was always the thing that got pushed to next sprint.
Solution
- Connected GitHub releases and the Notion product roadmap so the system knows when something ships.
- Added a relevance scorer using Claude that decides which updates are worth announcing and to whom.
- Set up content generation for blog posts, social posts, changelog entries, and email snippets.
- Configured routing so each piece goes to the right platform based on update type.
- Added a Notion review step so a human signs off before anything goes live.
Tools Used
- GitHub: Watches releases, PRs, and changelog commits to know when features ship.
- Notion: Where drafts land for review before publishing.
- Claude API: Scores relevance, writes content in different formats, and adjusts tone per channel.
- Make.com: Ties GitHub to Claude to Notion to the publishing channels.
Results
- <24 hrs Ship to Publish - Content is live within a day of a feature shipping. Used to take weeks.
- 4x Content Output - Four times more content per launch, same team size.
- 100% Launches Covered - Every feature gets announced. No more silent releases.
- 10 min Review to Publish - Drafts show up ready to go. Just needs a quick review.
Result: Under 24 hours from shipping a feature to having content live.
AI Hiring Pipeline - 25 hrs Saved Per Hire
Industry: Cross-industry. Category: Internal Operations. Timeline: 4 weeks.
Finds candidates, screens them with AI, books interviews, and learns from every hire and rejection. The whole loop runs itself.
We wired up a hiring pipeline that sources candidates, scores them against role criteria, schedules interviews on its own, and gets better at screening the more you use it.
Challenge: The team was burning 25+ hours per hire on admin work. Sourcing, screening resumes, going back and forth on scheduling, collecting feedback in random docs.
Solution
- Set up Clay to find and enrich candidate profiles matching role criteria.
- Connected Lemlist to run personalized outreach sequences to candidates.
- Added AI screening with Claude that scores candidates against the role's specific requirements.
- Automated interview scheduling through Google Calendar with timezone detection and availability sync.
- Plugged in Fireflies to record interviews and write AI summaries with the key evaluation points.
- Built a feedback loop so hiring outcomes feed back into scoring. The system gets better with each hire.
Tools Used
- Lemlist: Runs personalized outreach sequences to candidates.
- Clay: Finds profiles matching role criteria and enriches them with relevant data.
- Fireflies: Records interviews and writes AI summaries with evaluation notes.
- Google Calendar: Books interviews automatically, handles timezones and availability.
Results
- 0 Emails to Book - Interviews get booked without anyone sending a scheduling email.
- AI Screening - Each candidate gets scored against the role criteria, with reasoning attached.
- Self Improving - Every hire and rejection makes the screening more accurate.
- Full Loop Automated - Source, screen, schedule, interview, feedback. The whole loop runs hands-off.
Result: Nobody sends a single email to book an interview anymore.
Our stack - 50+ tools. And whatever else you throw at us.
We work with the tools you already use and connect them into systems that actually talk to each other.
Automation & AI
Make.com, n8n, Zapier, OpenAI, Claude, Gemini, Cursor, Replit, Perplexity, Fireflies, ElevenLabs.
CRM, Sales & Enrichment
HubSpot, Pipedrive, Folk, Apollo.io, Clay, Sales Navigator, Lemlist, Instantly, LaGrowthMachine, Smartlead, Clearbit, Kaspr, Lusha, Hunter.io, ZeroBounce, PhantomBuster.
Analytics & Data
Mixpanel, Google Analytics, Meta Ads, Metabase, Looker Studio, Stripe, Google Sheets, Airtable, Supabase.
Growth & Marketing
Mailchimp, Hootsuite, Semrush, Ahrefs, Loom.
Support, Comms & PM
Intercom, Zendesk, Slack, Notion, Linear, Asana, ClickUp, Google Calendar.
Web, Design & Scheduling
Webflow, Framer, Figma, Canva, GitHub, Firebase, Vercel, Calendly, Cal.com.
Ok so why us - We've been the firefighters inside the startup. The ones who get called when things are on fire.
That's why we don't start with tools. We start with the problem.
You don't need an elaborate brief. Just tell us what's not working. We'll figure out why, build the fix with AI, and make sure it keeps running as you grow.
Kshitij Maheshwari - Co-founder
Education: SRCC, ESSEC, Haas.
“I've been the first operator inside multiple AI startups and helped take them from nothing to real traction. I love figuring out how to make things work when no playbook exists yet.”
LinkedIn: https://www.linkedin.com/in/kmah11/
Rahul Bageria - Co-founder
Education: SRCC, ESSEC, Kellogg.
“I learned how systems should work at AWS and Accenture. Then I jumped into early-stage startups to build them from scratch. I'm happiest bringing structure to chaos without slowing things down.”
LinkedIn: https://www.linkedin.com/in/bageriarahul/
Got questions? We get these a lot.
- Who is this for?
- Early-stage startups and traditional businesses moving to modern tools. Teams of 5 to 100 people, from early stage to starting to scale. If your workflows feel messy, fragmented, or held together manually and it’s starting to bottleneck growth, we’re built for you.
- How is this different from hiring a freelancer or another AI agency?
- Most freelancers and agencies expect you to show up with a defined scope. We don’t. We are operators ourselves, and we’ve been the person inside the startup solving these exact problems. You get a real thinking partner, not just a vendor.
- What if I don’t know exactly what I need?
- Completely normal. That’s actually where we do our best work. You don’t need a brief or a project plan. Just walk us through your current workflows, what’s working, and what isn’t. We start with a diagnostic to find the root causes.
- What does the free audit include?
- A 30-minute diagnostic call. We review your current setup, identify bottlenecks, and highlight quick wins. You walk away with a clear picture of what’s fixable, an outside perspective on your operations, and honest recommendations. No pitch deck. No pressure.
- How long does a typical project take?
- Depends on complexity. Simple automations or dashboards: 1–2 weeks. End-to-end systems like outreach pipelines or support automation: 3–4 weeks. Advanced builds with self-improving AI: 4+ weeks.
- How do you price projects?
- By project, not by the hour. After the initial audit, we scope the work and give you a fixed price. No hidden costs, no surprises. Most projects start at $3,000 and go up based on scope and complexity.
- It’s just the two of you. Can you handle this?
- Yes, and that’s intentional. We’ve both operated as the single owner of ops, growth, and systems inside fast-moving startups. You work directly with us on every project, not a junior team you never met.
- What if it doesn’t work?
- Every project starts with clear scope alignment and defined deliverables. We include a testing and adjustment phase before handover. You try it, we refine it, and we don’t hand it over until it works. After that, you own everything. No lock-in.