Investor view
The AI Performance Reward OS for SMEs.
vimigo connects company direction, team execution, AI in real work, and a system that runs performance rewards and company data every day. Five products, each with its own task.
Investment thesis
Why this matters
Advanced AI is increasingly accessible, but companies still need workflow discovery, data and system connection, rollout, adoption and ongoing review.
- 01
The deployment gap
Access to AI is growing, while workflow redesign, data readiness, ownership and adoption remain difficult.
- 02
The SME gap
SMEs need implementation depth, but traditional one-enterprise-at-a-time deployment is difficult to afford and scale.
- 03
The vimigo model
Direction, performance, reward and adoption form the operating layer around AI-assisted workflows.
Product stack
Five products, one delivery engine
CEO, Team, AI Team, vimigo Software and CVO each carry their own task. Forward-deployed delivery works across all five.
Target model · To be validated through deployments
A services-to-software learning loop
The target operating model uses industry blueprints, reusable workflow patterns, connectors, governance and a control tower to reduce repeated custom work over time.
- Step 01
More real workflows
- Step 02
More validated reusable patterns
- Step 03
Faster configuration
- Step 04
More recurring software and governance
Evidence before scale claims
What we will measure—not what we will assume
Each measure will be published with its definition, period and source once the records exist.
- 01
Time to first value
- 02
Production workflow adoption
- 03
Recurring revenue mix
- 04
Reusable component rate
- 05
Companies supported per FDE pod
- 06
Customer impact against agreed measures
Market context · Official 2025 data
SME AI transformation is a productivity infrastructure question.
Global deployment signals · Primary sources
The AI bottleneck is moving from model access to real workflow deployment.
These sources establish why deployment matters; they do not imply that OpenAI or Palantir partners with, endorses or validates vimigo.
- OpenAI
OpenAI made deployment a dedicated company-level capability
On 11 May 2026, OpenAI announced a Deployment Company built around teams working with business leaders, operators and frontline employees to redesign workflows and move AI into production systems.
This validates the importance of deployment. It does not validate vimigo’s delivery scale or outcomes.
Read the primary source · OpenAI · Deployment Company announcement - OpenAI
Forward-deployed work extends beyond software development
OpenAI describes the FDE role across discovery, technical scoping, system design, build and production rollout, with success tied to adoption, measurable workflow impact and reusable learning.
vimigo uses this as a delivery design reference, not as a claim of equivalence or affiliation.
Read the primary source · OpenAI · Forward Deployed Engineer role - Palantir
Fast use-case development is possible when delivery is structured
In a post of 12 October 2023, Palantir stated that its AIP Bootcamps can move from zero to a working use case in one to five days through an intensive, hands-on format.
That is Palantir’s own programme description—not proof of production ROI, SME fit or vimigo capability.
Read the primary source · Palantir · AIP Bootcamp methodology
The vision is clear. The evidence must be earned.
We intend to validate the model through deployment, adoption, reuse, recurring revenue and customer outcomes.