Osiris
Embedded AI ops team that designs, builds, and runs automations inside your stack.
Tagline
AI ops that actually ship
Production AI systems for messy operators
Your existing stack, rebuilt with AI
Kill the manual ops backlog
The applied AI studio for operators who need systems that survive contact with reality.
The page repeatedly emphasizes production use, evals, monitoring, runbooks, and on-call support, which differentiates it from demo-grade AI agencies and “chatbot builders.”
An alternative to buying another SaaS tool: Osiris rebuilds the workflow inside your existing stack.
The site stresses that it does not require tooling migration and works inside HubSpot, Salesforce, Zendesk, n8n, Make, and Zapier. That is a strong wedge against point solutions like LeanData, Chili Piper, Drift, or Intercom when the buyer wants custom behavior.
Kill the manual ops backlog: from lead routing to reconciliation, Osiris removes handoffs and repeat work.
The most concrete use cases are pain-killers: lead qualification, sales funnel automation, CRM hygiene, finance triage, support deflection, and marketing ops. This makes the value prop easy to sell to operators who buy time and reliability, not AI novelty.
Primary user
Head of Revenue Operations at a B2B SaaS company trying to clean up routing, scoring, and follow-up across HubSpot/Salesforce
ICP #1
Head of Revenue Operations at a 50-500 person B2B SaaS company using Salesforce or HubSpot
Pain
Lead routing is brittle, enrichment is inconsistent, reps do manual janitor work, and nobody trusts the CRM enough to automate deeper workflows.
Why this solves
Osiris explicitly builds CRM automation for HubSpot, Salesforce, Pipedrive, and Attio, including deduplication, enrichment, ownership routing, and autonomous follow-up, then stays on call to keep the system healthy.
ICP #2
COO of a fast-growing professional services or operations-heavy company
Pain
Internal teams are drowning in handoffs, exceptions, and spreadsheet-driven process glue that eats hours every day.
Why this solves
Osiris’s ops automation offer is built for process re-engineering without forcing a platform migration, which is exactly what COO-level operators want when they need leverage without a transformation project.
ICP #3
VP Support at a SaaS company with a Zendesk-heavy queue and a knowledge base that is good but underused
Pain
Tier-1 tickets still require humans for repetitive questions, while edge cases get lost or escalated without context.
Why this solves
Osiris’s support AI is designed to resolve high-confidence tickets from the knowledge base and escalate with full context when confidence is low, which reduces load without sacrificing quality control.
Strengths
- +Very specific service menu with clear examples tied to actual systems like HubSpot, Salesforce, Zendesk, n8n, Make, and Zapier
- +Strong credibility signal that this is not a one-and-done build shop: the operate/on-call offer is a meaningful differentiator
- +The page speaks the language of operators and revenue teams, not generic AI hype
Weaknesses
- −It reads like a high-end services studio, but there is no sharp wedge or signature use case that makes Osiris instantly memorable
- −The brand is visually polished but the value proposition is diffuse: AI strategy, agents, ops, CRM, integrations, custom apps, and ongoing support is too broad for a cold visitor
- −No hard proof beyond one testimonial; there are no quantified outcomes, logos, case studies, or before/after metrics
- −The page lacks pricing cues, engagement shape, or buyer qualification, so prospects cannot tell if this is enterprise consulting, a mid-market implementation partner, or a boutique agency
- −Competitor comparison is implicit but not explicit, so the visitor has to do the mental work of understanding why this is better than buying LeanData, Intercom, Zapier, or hiring a systems integrator
Fix these
- Pick one wedge and lead with it: for example, autonomous CRM and RevOps systems for B2B SaaS, then branch into adjacent services
- Add 3-4 case studies with exact metrics like time saved, lead response time reduced, ticket deflection rate, or reconciliation hours eliminated
- Show a before/after workflow diagram for one flagship use case, such as lead qualification or support triage, to make the transformation tangible
- Clarify engagement model upfront: typical timeline, team composition, starting price range, and what "operate & on-call" actually includes
- Add a proof-heavy section that compares Osiris against buying software plus internal implementation, so prospects understand why a studio is the right purchase
Drop-in replacement copy
Headline
AI ops that survive reality
We design, build, and run automations inside your stack.
Fix the workflow, not the tool
We build inside HubSpot, Salesforce, Zendesk, n8n, Make, and Zapier instead of forcing a migration. That means you get leverage without a platform change project.
Production systems, not demos
Every build includes evals, monitoring, human fallback paths, and rollback plans. If the model or provider changes behavior, the system still has a way to recover.
Own the ugly edge cases
We design for messy data, exceptions, and weird handoffs instead of pretending they do not exist. That is how automation becomes trusted by the team using it.
Stay healthy after launch
Osiris stays on call to keep the workflow running, update prompts, handle regressions, and improve the system as your business changes. You are not left with a dead handoff.
FAQ
Is Osiris software or a services team?
It is a senior implementation team. We design, build, and operate the automation inside your stack rather than handing you a license and a login.
What kinds of workflows do you take on?
RevOps, support ops, finance ops, and back-office processes with repeated manual steps, handoffs, or exception handling. If the workflow is messy, that is usually a good fit.
Do we need to replace HubSpot, Salesforce, Zendesk, or our automations?
No. We work inside the stack you already use and connect the systems around it.
How do you keep AI from breaking in production?
We use evals, monitoring, human review where needed, and clear rollback paths. The goal is not just to ship something clever, but to keep it safe and useful over time.
What does an engagement usually look like?
We start with a workflow teardown and implementation plan, then build the first system, then stay involved after launch. Most clients want a clear fix to one painful process before expanding to the next one.
Lead routing breaks. Enrichment is stale. Reps fix records by hand. That’s not a CRM problem. It’s an ops system problem. We build AI agents that clean up the mess inside HubSpot/Salesforce and keep running after launch.
We built Osiris for the opposite reason: to map the workflow, ship the automation, monitor it in production, and stay on call when reality gets weird. For teams who want AI that survives contact with ops.
The market does not need another prompt pack. It needs someone who can debug lead routing, exception handling, CRM hygiene, and support triage inside the stack people already use. That’s what we’re building at Osiris.
High-confidence tickets get answered from the KB. Low-confidence tickets get escalated with full context. No tool migration. No bot theater. Just fewer repetitive tickets and better handoffs.
"It finally works without babysitting." That’s the bar. Not a flashy demo. A workflow that keeps working after the founders stop staring at it.
If reps are still doing lead janitor work, your pipeline is leaking. Routing, enrichment, scoring, follow-up, retries. We turn that into a system instead of a Slack reminder.
Osiris is an applied AI studio. We design, build, and run automations inside your stack. If you want software licensing, buy software. If you want the workflow fixed, bring us the mess.
The secret is not the model. It’s evals, runbooks, monitoring, human-in-the-loop review, and fast rollback when a provider changes behavior. Boring discipline is what makes AI useful.
They buy fewer handoffs. Fewer exceptions. Fewer spreadsheet bridges. That’s why our best conversations start with one question: What process is eating your team alive right now?
An inbound lead lands. It gets enriched, scored, routed, and followed up. If the data is messy, the agent flags it instead of guessing. That’s the difference between a demo and production.
Angle: The applied AI studio for operators who need systems that survive reality
Most AI projects fail for a boring reason: They were built like demos, not operations. A chatbot that answers a few clean questions is easy. A system that survives dirty data, weird edge cases, changing tools, and human exceptions is the hard part. That’s why we built Osiris as an applied AI studio for operators. We don’t sell “AI strategy” in the abstract. We map the workflow, decide what should be automated, build the agents and integrations, then stay on call after launch so the thing keeps working in production. The work usually starts with one ugly process: - lead routing that nobody trusts - CRM hygiene that lives in spreadsheets - support triage that burns the team - finance ops that depend on manual reconciliation The goal is simple: remove handoffs, reduce repetitive work, and make the system reliable enough that people actually use it. If your team has a process that is held together by memory, Slack, and one heroic ops person, that is probably the right place to start.
Angle: Osiris as the alternative to buying yet another SaaS tool
A lot of teams do not need another tool. They need their existing stack to behave like a system. That is the wedge for Osiris. If you are already living in HubSpot, Salesforce, Pipedrive, Attio, Zendesk, n8n, Make, Zapier, and a pile of internal rules, the problem is rarely a lack of software. It is usually: - inconsistent data - brittle handoffs - missing business logic - automations that break the second reality gets messy We rebuild the workflow inside the tools you already use. That means less migration risk, less training overhead, and less “we’ll do this after the next quarter” drag. For a RevOps lead, that might mean autonomous lead qualification and routing. For a support leader, it might mean tier-1 deflection with safe escalation. For an ops team, it might mean exception handling without spreadsheet glue. The point is not to add more software. The point is to remove the manual work your software never solved.
Angle: Why boring production discipline matters more than flashy AI
The market is full of people selling AI novelty. We are more interested in AI that does not embarrass you on a Tuesday. Production AI is mostly boring: - evals - monitoring - rollback plans - prompt updates - provider changes - human-in-the-loop review when confidence is low That boring stuff is what keeps systems alive after launch. At Osiris, we keep seeing the same pattern: teams want the upside of automation, but they also want someone to own the mess when the edge cases show up. That is the real product. Not just the build. The operating model. If you are a RevOps, Support Ops, or COO leader and your team is drowning in handoffs, exceptions, and manual follow-up, the question is not whether AI is possible. The question is whether it will still be safe and useful three months from now. That is the bar we build to.
Tagline
Applied AI ops team for messy workflows
Description
Osiris designs, builds, and runs AI automations inside your existing stack. Built for RevOps, support, finance, and ops teams that want real production workflows, not demo bots.
Maker's first comment
We built Osiris because too many AI projects stop at the demo. I kept seeing the same pattern: a team would get excited about automation, ship something flashy, and then two weeks later the workflow was broken because the data was messy, the exceptions were real, and nobody owned the operating layer. Osiris is our answer to that gap. We embed with operators, map the process, build the agents and integrations, and then stay on call after launch so the system keeps working in production. Most of the work is not glamorous. It is routing rules, human review paths, evals, monitoring, rollback plans, and fixing the boring stuff that makes AI reliable. We started with use cases like lead qualification, CRM cleanup, support deflection, and back-office automation because those are the places where teams feel pain every day. Would love feedback from people running RevOps, Support Ops, or internal ops teams: what workflow would you trust an external team to own end-to-end?
Pinned maker comment
Would love feedback on the wedge: should we lean hardest into RevOps automation for B2B SaaS, or keep the broader ops offer?
Meta
Your CRM still needs a human janitor
Hypothesis: RevOps leaders at 50-500 person B2B SaaS companies will click because they want lead routing, enrichment, and follow-up fixed inside HubSpot or Salesforce without buying another tool. Osiris maps the workflow, builds the automation, and stays on call after launch.
Google Search
AI automation for HubSpot and Salesforce
Hypothesis: buyers searching for implementation help are not looking for software; they want someone to make their current CRM work. Osiris designs, builds, and operates AI workflows for lead routing, support triage, and ops automation inside your stack.
Reddit Promoted
If your ops team lives in spreadsheets, read this
Hypothesis: operators in r/RevOps, r/SaaS, and r/sales will engage with a post about fixing manual handoffs because the pain is immediate and specific. We build AI agents and automations inside HubSpot, Salesforce, Zendesk, n8n, Make, and Zapier, then monitor them in production.
Subreddits
r/RevOps
Share a teardown of brittle lead routing and what a production-safe AI workflow looks like
Rules: No drive-by self-promo; post a useful breakdown, examples, or lessons learned rather than a sales pitch
r/sales
Lead qualification and follow-up automation that helps reps spend less time on janitor work
Rules: Must be practical and sales-relevant; avoid pure marketing language and obvious promotion
r/SaaS
How SaaS teams can automate ops without migrating off their current stack
Rules: Value-first posts work best; do not lead with a product link or hypey launch language
r/Entrepreneur
Founder story about removing manual ops overhead and buying back team time
Rules: Needs a real story or lesson; self-promo is usually removed unless it is clearly educational
r/automation
Production automation lessons: evals, monitoring, and human fallback paths
Rules: Share implementation detail and concrete examples; users are skeptical of vague automation claims
Communities
Post operator-focused breakdowns of workflows, metrics, and what broke in production. Comment on automation and B2B SaaS threads daily before posting your own product.
Join discussions about routing, scoring, and CRM hygiene; share tactical before/after examples and avoid pitching until people ask.
Use it for peer-level conversations with revenue leaders. Offer teardown help on process design, not product features.
SaaS Operators
Share playbooks for back-office automation, support deflection, and RevOps cleanup; be the person posting useful checklists and failure modes.
Cold outreach template
Hey {firstName} - noticed {context}. If lead routing / follow-up / CRM hygiene is still eating ops time, we map the workflow and build the automation inside your current stack. Happy to send a 5-minute teardown of where the manual work is hiding.
Product Hunt timing
Launch on Tuesday at 12:01am Pacific Time. PH traffic is strongest early in the U.S. workday, and this ICP is operator-heavy, so you want East Coast buyers checking it before their morning meetings and West Coast teams seeing it before lunch.
Indie Hackers post ideas
- 01We replaced spreadsheet ops glue with AI automations: what actually broke in production
- 02How to know if your CRM problem is really a workflow problem
- 03Evals, monitoring, and rollback plans for AI agents inside RevOps
Competitor alternatives
Current tone of voice
Confident, senior, and operator-first with a slightly mystical brand wrapper; for example: "Bring us your messiest process" and "the boring runbook discipline that keeps AI working in production."
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