Planhat: Your Commercial AI System
Planhat: Your Commercial AI System
Planhat: Your Commercial AI System
Planhat: Your Commercial AI System
Practical AI for Commercial Teams: building the system, not just the agent
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AI will transform how enterprises do work, ultimately lifting both revenue and efficiency—yet most enterprise pilots stall.
The gap isn’t models; it’s missing knowledge + tools to anchor AI in your business, to go beyond controlled pilots.
At Planhat, we’ve spent a decade making commercial teams more effective and efficient, and built the platform so the "ingredients" for intelligent automation—complete customer context, comprehensive actions, model interoperability—were ready as foundational model capabilities are exploding.
On the knowledge side, we’ve spent a decade advising commercial organisations on how to leverage software to make their teams move faster—and we bring that knowledge into a new era.
Our AI approach, combining tools (AI Platform) and knowledge (AI Deployment Program) is the natural evolution of our broader platform strategy, but bringing a targeted approach for a new era to help you win in this next era.
There is no doubt that AI will transform the enterprise, and we think it will just further root you in the core of your business: the customer. In this article, we will share our current thinking on how this will develop—and importantly, how this can deliver value for you today.
AI will transform how enterprises do work, ultimately lifting both revenue and efficiency—yet most enterprise pilots stall.
The gap isn’t models; it’s missing knowledge + tools to anchor AI in your business, to go beyond controlled pilots.
At Planhat, we’ve spent a decade making commercial teams more effective and efficient, and built the platform so the "ingredients" for intelligent automation—complete customer context, comprehensive actions, model interoperability—were ready as foundational model capabilities are exploding.
On the knowledge side, we’ve spent a decade advising commercial organisations on how to leverage software to make their teams move faster—and we bring that knowledge into a new era.
Our AI approach, combining tools (AI Platform) and knowledge (AI Deployment Program) is the natural evolution of our broader platform strategy, but bringing a targeted approach for a new era to help you win in this next era.
There is no doubt that AI will transform the enterprise, and we think it will just further root you in the core of your business: the customer. In this article, we will share our current thinking on how this will develop—and importantly, how this can deliver value for you today.
AI will transform how enterprises do work, ultimately lifting both revenue and efficiency—yet most enterprise pilots stall.
The gap isn’t models; it’s missing knowledge + tools to anchor AI in your business, to go beyond controlled pilots.
At Planhat, we’ve spent a decade making commercial teams more effective and efficient, and built the platform so the "ingredients" for intelligent automation—complete customer context, comprehensive actions, model interoperability—were ready as foundational model capabilities are exploding.
On the knowledge side, we’ve spent a decade advising commercial organisations on how to leverage software to make their teams move faster—and we bring that knowledge into a new era.
Our AI approach, combining tools (AI Platform) and knowledge (AI Deployment Program) is the natural evolution of our broader platform strategy, but bringing a targeted approach for a new era to help you win in this next era.
There is no doubt that AI will transform the enterprise, and we think it will just further root you in the core of your business: the customer. In this article, we will share our current thinking on how this will develop—and importantly, how this can deliver value for you today.
Planhat AIP: agents anchored in your reality
Most “agent builders” stop at the bot itself, or purpose-build bots for specific cases. But value comes from anchoring that bot in your context, goals, expertise, and team—and then doing that at scale, across the hundreds of use cases that compound to transform your business.
Our product vision for AIP brings three pieces together:
Agent Builder (incl. Model Hub, MCP server): build enterprise-ready AI workflows and agents in minutes, like Account Risk manager or auto-generating enriched opportunities to your sales team
Agent Enabler: our internal set of system modules that natively power all your AI workflows, with the deep domain expertise needed for true autonomy (eg, dynamic understanding of people relationship and influence in your org)
Native Platform Integration: connected Planhat’s data, automation, and collaboration layers; this is critical, because a lot of the value of AI will come from integrating into end-to-end workflows
Unlike many competing tools, we haven’t taken a point-solution approach to AI (eg, just building a call recorder, or a churn risk predictor). We think the potential for AI to transform any business process, coupled with the uniqueness of each organisation, means you have to take a tools- and context-centric approach to developing the AI platform - but with templating, you can still get up and running as-fast.
This means that with our AIP you can solve hundreds of use cases, like:
Automatic call transcript summaries, incl. recommended next steps, based on your context
eg not just a context-less summary, but weighted based on everything we know about the customer, their issues/tickets, their feedback, their people and their decision power, etc
Risk Agents and AI-driven health scores, continuously monitoring conversational data (eg, tickets, emails, calls), usage data, and active projects/sequences for signals - to flag risk earlier
Automated account research for sales and CS, to automate meeting preparation and save reps hours every week
Auto-generating Opportunities based on signals in emails/calls/tickets/metrics, then enriching the opportunities and looping in the right team to execute fast
As we keep expanding agentic tools and accessible context, which is the main roadmap focus for our next 12-18 months, the number of use cases that can be solved explodes. Read about our September releases [here], as part of this Journal.
Fundamentally, this is not a stitched-on AI product; it’s a deeply integrated work platform that models itself after your context and workflows, with agents embedded from first marketing contact to account expansion. This means you can deploy AI faster, more securely, and more scalable across processes.
Planhat AIP: agents anchored in your reality
Most “agent builders” stop at the bot itself, or purpose-build bots for specific cases. But value comes from anchoring that bot in your context, goals, expertise, and team—and then doing that at scale, across the hundreds of use cases that compound to transform your business.
Our product vision for AIP brings three pieces together:
Agent Builder (incl. Model Hub, MCP server): build enterprise-ready AI workflows and agents in minutes, like Account Risk manager or auto-generating enriched opportunities to your sales team
Agent Enabler: our internal set of system modules that natively power all your AI workflows, with the deep domain expertise needed for true autonomy (eg, dynamic understanding of people relationship and influence in your org)
Native Platform Integration: connected Planhat’s data, automation, and collaboration layers; this is critical, because a lot of the value of AI will come from integrating into end-to-end workflows
Unlike many competing tools, we haven’t taken a point-solution approach to AI (eg, just building a call recorder, or a churn risk predictor). We think the potential for AI to transform any business process, coupled with the uniqueness of each organisation, means you have to take a tools- and context-centric approach to developing the AI platform - but with templating, you can still get up and running as-fast.
This means that with our AIP you can solve hundreds of use cases, like:
Automatic call transcript summaries, incl. recommended next steps, based on your context
eg not just a context-less summary, but weighted based on everything we know about the customer, their issues/tickets, their feedback, their people and their decision power, etc
Risk Agents and AI-driven health scores, continuously monitoring conversational data (eg, tickets, emails, calls), usage data, and active projects/sequences for signals - to flag risk earlier
Automated account research for sales and CS, to automate meeting preparation and save reps hours every week
Auto-generating Opportunities based on signals in emails/calls/tickets/metrics, then enriching the opportunities and looping in the right team to execute fast
As we keep expanding agentic tools and accessible context, which is the main roadmap focus for our next 12-18 months, the number of use cases that can be solved explodes. Read about our September releases [here], as part of this Journal.
Fundamentally, this is not a stitched-on AI product; it’s a deeply integrated work platform that models itself after your context and workflows, with agents embedded from first marketing contact to account expansion. This means you can deploy AI faster, more securely, and more scalable across processes.
Planhat AIP: agents anchored in your reality
Most “agent builders” stop at the bot itself, or purpose-build bots for specific cases. But value comes from anchoring that bot in your context, goals, expertise, and team—and then doing that at scale, across the hundreds of use cases that compound to transform your business.
Our product vision for AIP brings three pieces together:
Agent Builder (incl. Model Hub, MCP server): build enterprise-ready AI workflows and agents in minutes, like Account Risk manager or auto-generating enriched opportunities to your sales team
Agent Enabler: our internal set of system modules that natively power all your AI workflows, with the deep domain expertise needed for true autonomy (eg, dynamic understanding of people relationship and influence in your org)
Native Platform Integration: connected Planhat’s data, automation, and collaboration layers; this is critical, because a lot of the value of AI will come from integrating into end-to-end workflows
Unlike many competing tools, we haven’t taken a point-solution approach to AI (eg, just building a call recorder, or a churn risk predictor). We think the potential for AI to transform any business process, coupled with the uniqueness of each organisation, means you have to take a tools- and context-centric approach to developing the AI platform - but with templating, you can still get up and running as-fast.
This means that with our AIP you can solve hundreds of use cases, like:
Automatic call transcript summaries, incl. recommended next steps, based on your context
eg not just a context-less summary, but weighted based on everything we know about the customer, their issues/tickets, their feedback, their people and their decision power, etc
Risk Agents and AI-driven health scores, continuously monitoring conversational data (eg, tickets, emails, calls), usage data, and active projects/sequences for signals - to flag risk earlier
Automated account research for sales and CS, to automate meeting preparation and save reps hours every week
Auto-generating Opportunities based on signals in emails/calls/tickets/metrics, then enriching the opportunities and looping in the right team to execute fast
As we keep expanding agentic tools and accessible context, which is the main roadmap focus for our next 12-18 months, the number of use cases that can be solved explodes. Read about our September releases [here], as part of this Journal.
Fundamentally, this is not a stitched-on AI product; it’s a deeply integrated work platform that models itself after your context and workflows, with agents embedded from first marketing contact to account expansion. This means you can deploy AI faster, more securely, and more scalable across processes.
Planhat ADP: services that make AI stick
AI is a tool, not something valuable in itself.
As many have written about, from A16Z to McKinsey & Co, true value capture of AI will come from organisations’ ability to transform the way they operate and run workflows using AI - and that requires someone to deeply understand your business, your pain points, and help you solve them. This is what we do.
ADP (AI Deployment Program) is our specialist hub that covers your entire AI deployment journey, from the first steps and experiments to end-to-end business transformation.
ADP is run by a task-force of professional operators, not consultants. Veterans in the arena of customer management collaborate with technologists who've spent their careers building at the frontier of cloud software to embed AI meaningfully into your organization.
We’ve helped customers to reach goals like:
Increase revenue managed by account rep, through introducing account risk monitors
Shorten deal cycles, by automating data enrichment and research
Reduce onboarding times, by making parts more self-serve and with better process management
To learn more, read more about the ADP [here].
Planhat ADP: services that make AI stick
AI is a tool, not something valuable in itself.
As many have written about, from A16Z to McKinsey & Co, true value capture of AI will come from organisations’ ability to transform the way they operate and run workflows using AI - and that requires someone to deeply understand your business, your pain points, and help you solve them. This is what we do.
ADP (AI Deployment Program) is our specialist hub that covers your entire AI deployment journey, from the first steps and experiments to end-to-end business transformation.
ADP is run by a task-force of professional operators, not consultants. Veterans in the arena of customer management collaborate with technologists who've spent their careers building at the frontier of cloud software to embed AI meaningfully into your organization.
We’ve helped customers to reach goals like:
Increase revenue managed by account rep, through introducing account risk monitors
Shorten deal cycles, by automating data enrichment and research
Reduce onboarding times, by making parts more self-serve and with better process management
To learn more, read more about the ADP [here].
Planhat ADP: services that make AI stick
AI is a tool, not something valuable in itself.
As many have written about, from A16Z to McKinsey & Co, true value capture of AI will come from organisations’ ability to transform the way they operate and run workflows using AI - and that requires someone to deeply understand your business, your pain points, and help you solve them. This is what we do.
ADP (AI Deployment Program) is our specialist hub that covers your entire AI deployment journey, from the first steps and experiments to end-to-end business transformation.
ADP is run by a task-force of professional operators, not consultants. Veterans in the arena of customer management collaborate with technologists who've spent their careers building at the frontier of cloud software to embed AI meaningfully into your organization.
We’ve helped customers to reach goals like:
Increase revenue managed by account rep, through introducing account risk monitors
Shorten deal cycles, by automating data enrichment and research
Reduce onboarding times, by making parts more self-serve and with better process management
To learn more, read more about the ADP [here].
Deploying AI: starting focused and simple
As of mid-2025, 95% of enterprise AI pilots fail.
Planhat is a company founded with an operator mindset: get to real outcomes fast, with the resources available to you. This has also shaped our approach to AI deployment.
At the core, use a simple lens: ACV × level of automation.
High-ACV accounts (>$10k): aim for assistive AI—research, enrichment, meeting prep/follow-up, signals—with a human in the loop. Cost of error is high; upside is higher.
Low-ACV accounts (<$1k): push toward autonomous workflows—ticket/email triage, renewals—where automation ROI outweighs occasional error.
Within these simplistic boundaries, you can quickly deploy 10s of AI workflows using our templates— which will help you familiarise yourself with how AI workflows are built and maintained.
We’ve developed our own CRAWL/WALK/RUN packages that help you navigate the AI adoption journey in a self-serve and best-practice way - just reach out to your CSM/TDL to get started.
Deploying AI: starting focused and simple
As of mid-2025, 95% of enterprise AI pilots fail.
Planhat is a company founded with an operator mindset: get to real outcomes fast, with the resources available to you. This has also shaped our approach to AI deployment.
At the core, use a simple lens: ACV × level of automation.
High-ACV accounts (>$10k): aim for assistive AI—research, enrichment, meeting prep/follow-up, signals—with a human in the loop. Cost of error is high; upside is higher.
Low-ACV accounts (<$1k): push toward autonomous workflows—ticket/email triage, renewals—where automation ROI outweighs occasional error.
Within these simplistic boundaries, you can quickly deploy 10s of AI workflows using our templates— which will help you familiarise yourself with how AI workflows are built and maintained.
We’ve developed our own CRAWL/WALK/RUN packages that help you navigate the AI adoption journey in a self-serve and best-practice way - just reach out to your CSM/TDL to get started.
Deploying AI: starting focused and simple
As of mid-2025, 95% of enterprise AI pilots fail.
Planhat is a company founded with an operator mindset: get to real outcomes fast, with the resources available to you. This has also shaped our approach to AI deployment.
At the core, use a simple lens: ACV × level of automation.
High-ACV accounts (>$10k): aim for assistive AI—research, enrichment, meeting prep/follow-up, signals—with a human in the loop. Cost of error is high; upside is higher.
Low-ACV accounts (<$1k): push toward autonomous workflows—ticket/email triage, renewals—where automation ROI outweighs occasional error.
Within these simplistic boundaries, you can quickly deploy 10s of AI workflows using our templates— which will help you familiarise yourself with how AI workflows are built and maintained.
We’ve developed our own CRAWL/WALK/RUN packages that help you navigate the AI adoption journey in a self-serve and best-practice way - just reach out to your CSM/TDL to get started.
What “AI-leading” operations look like
Taking a step back, how will leading teams operate in 6-18 months, as the value of 10s or 100s of AI workflows start to compound?
Ultimately, AI-leading orgs will move faster and do more with fewer people because objectives and context flow-through systems, not only managers:
Faster adaptation: goals translate into behavior programmatically; continuous monitoring adjusts actions in-flow.
Throughput: repeatable work becomes agent-led; humans handle strategy, relationships, and edge cases.
Manual data entry evolves: mind-numbing fields go away; high-value context sharing becomes the main objective.
Rise of orchestrators: RevOps-style teams steer narratives, playbooks, and artifacts that guide frontline agents across the lifecycle.
Platforms, like Planhat, simplify: two cores remain—agent orchestration (context engineering, artifacts, actions) and human/agent collaboration (Slack, Teams). Collaboration data becomes the richest feed for mapping organisational power structures and best practices.
Most of all, deploying AI in the enterprise will be a journey—and we’re very much looking forward to partnering and collaborating with you in figuring this new world out.
We're scaling up AI-focused teams in Product, Engineering, Marketing and ADP - reach out if you're a crafty builder who want to go beyond the "cool app" and truly shape the way enterprises will operate for years to come.
What “AI-leading” operations look like
Taking a step back, how will leading teams operate in 6-18 months, as the value of 10s or 100s of AI workflows start to compound?
Ultimately, AI-leading orgs will move faster and do more with fewer people because objectives and context flow-through systems, not only managers:
Faster adaptation: goals translate into behavior programmatically; continuous monitoring adjusts actions in-flow.
Throughput: repeatable work becomes agent-led; humans handle strategy, relationships, and edge cases.
Manual data entry evolves: mind-numbing fields go away; high-value context sharing becomes the main objective.
Rise of orchestrators: RevOps-style teams steer narratives, playbooks, and artifacts that guide frontline agents across the lifecycle.
Platforms, like Planhat, simplify: two cores remain—agent orchestration (context engineering, artifacts, actions) and human/agent collaboration (Slack, Teams). Collaboration data becomes the richest feed for mapping organisational power structures and best practices.
Most of all, deploying AI in the enterprise will be a journey—and we’re very much looking forward to partnering and collaborating with you in figuring this new world out.
We're scaling up AI-focused teams in Product, Engineering, Marketing and ADP - reach out if you're a crafty builder who want to go beyond the "cool app" and truly shape the way enterprises will operate for years to come.
What “AI-leading” operations look like
Taking a step back, how will leading teams operate in 6-18 months, as the value of 10s or 100s of AI workflows start to compound?
Ultimately, AI-leading orgs will move faster and do more with fewer people because objectives and context flow-through systems, not only managers:
Faster adaptation: goals translate into behavior programmatically; continuous monitoring adjusts actions in-flow.
Throughput: repeatable work becomes agent-led; humans handle strategy, relationships, and edge cases.
Manual data entry evolves: mind-numbing fields go away; high-value context sharing becomes the main objective.
Rise of orchestrators: RevOps-style teams steer narratives, playbooks, and artifacts that guide frontline agents across the lifecycle.
Platforms, like Planhat, simplify: two cores remain—agent orchestration (context engineering, artifacts, actions) and human/agent collaboration (Slack, Teams). Collaboration data becomes the richest feed for mapping organisational power structures and best practices.
Most of all, deploying AI in the enterprise will be a journey—and we’re very much looking forward to partnering and collaborating with you in figuring this new world out.
We're scaling up AI-focused teams in Product, Engineering, Marketing and ADP - reach out if you're a crafty builder who want to go beyond the "cool app" and truly shape the way enterprises will operate for years to come.
A New Dawn
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