Core Offerings
Deepgrain structures its work around three primary starting points for teams that want to adopt AI without forcing generic role-replacement frameworks. It focuses on atomic, click-level workflow mapping rather than broad role audits to identify where AI can cut redundant manual work.
People Function Readiness Assessment: A 10-minute assessment that generates an objective baseline of where a company's People function stands on AI adoption.
AI Exposure Map: An interactive tool that shows which G&A functions are already reachable with AI, and which still require full human ownership.
People Ops AI Brain: A public explanation of Deepgrain's four-layer operating model that breaks down how AI can integrate with People operations.
Paid Programs & Engagements
Grain Audit: A 2-week engagement where the Deepgrain team maps one full business workflow, documents its existing atomic steps, and delivers 3 prioritized actionable changes the company can implement immediately.
AI Cohort for People Teams: A 4-week live program limited to 20 seats, where participants build 3 working AI automations for their own internal processes and leave with a 90-day company-wide rollout plan. The listed price for waitlist members is £495.
Custom Business Training: Dedicated AI training sessions designed for entire in-house business teams.
Full Build Engagements: Typically 8 to 16 weeks per function, where Deepgrain works end-to-end to redesign targeted workflows, deploy custom AI agents, and upskill the internal team to maintain the systems independently.
Key Workflow Redesign Approach
Deepgrain uses a proven joiner-to-first-pay-run workflow example to demonstrate its methodology:
Before redesign, the workflow required 0 minutes of high-value handling per new joiner, most of it spent on rekeying data and chasing updates across 3 systems, 4 handoffs, across 14 total atomic steps.
After redesign and automation, the total number of steps drops to 9, with 5 redundant steps fully cut. An AI agent assembles all the required data, while humans only complete the two high-judgement eligibility checks and final sign-off. No judgement or accountability steps are automated.
Non-Negotiable Guardrails for AI Implementation
Deepgrain explicitly defines three categories of work that will never be automated in client workflows:
Judgement calls: Decisions around risk, role assignments, and fairness stay fully under human control. AI only drafts supporting materials, and a human retains final sign off.
Accountability: A named person remains responsible for every AI system, its outputs, its auditing schedule, and its data hosting location. No automated system is allowed to take ownership of outcomes.
Human relationships: Hard conversations, trust building, and in-person context assessment for teams are kept as human-led activities.
The company states that teams that automate all judgement work do not become more resilient, they become brittle and operationally deniable.
Target Audience
Deepgrain works primarily with founder-led companies in the Series A to Series C stage across sectors including AI-native tools, defence, financial data, transit, and climate technology. It is built for operating leaders and People heads who want to implement practical, production-grade AI workflows rather than run isolated demo AI tools that do not integrate with day-to-day operations.
Expected Business Outcomes
Teams that implement Deepgrain's workflow redesign and AI systems can realize three categories of value:
Avoid new hires that would otherwise be required to handle growing administrative load
Absort business growth without increasing headcount cost
Redeploy existing senior team members away from repetitive data entry work onto high-judgement tasks that directly move core business metrics
A 40-person function that reclaims 30 minutes per person per week from redundant manual work recovers roughly one full equivalent of senior capacity to reallocate.
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