AI agents and domain experts
SHIFTLABS pairs AI agents, which interview your teams and measure real work, with experts who validate every conclusion. Nothing ships without their sign-off. Diagnosis, quantified use cases and roadmap in two weeks.
Who we are, what we do
SHIFTLABS is an AI transformation platform, run by a data and AI consultant with domain experts engaged for each assignment. In two weeks, we find where AI will save your teams time; then you steer the rollout in an online cockpit.
Léa, our interview agent, asks your people about the work they actually do. She introduces herself as an AI and never assesses individuals.
You receive: A map of the real work
Each task is measured in time spent, then each use case is scored on impact, feasibility and cost.
You receive: Prioritised, quantified use cases
The agents produce drafts. An expert reviews and signs them off: nothing reaches you without that signature.
You receive: Validated conclusions
Roadmap, estimated gains and adoption are tracked in an online cockpit, updated as the rollout progresses.
You receive: The roadmap and its tracking
No call required
Three ways to try SHIFTLABS right now, without sending any data.
Recoverable hours, annual value and payback period of a first AI agent, from seven adjustable assumptions.
Twelve questions, six dimensions, four tiers: place your organisation’s AI maturity in three minutes.
An interview with Léa, replayed step by step: fictional content, no AI call.
AI agents carry out the analytical work across the whole company; human experts validate every deliverable before it reaches you.
AI agents handle the analytical volume; a senior consultant validates every deliverable. The flow is colour-coded: at each step, you know who does what, and where human judgement takes over.
What you open up to us
AI-agent interviews · Business logs (ERP / CRM / ticketing) · Usage telemetry
Analytical work at scale
The human safeguard
What your board receives
What you open up to us
Analytical work at scale
Exception branch: human-in-the-loopAmbiguous or high-stakes case detected by the agents (02) → human decision, then back into expert validation (03).
The human safeguard
What your board receives
Exception branch: human-in-the-loopAmbiguous or high-stakes case detected by the agents (02) → human decision, then back into expert validation (03).
In a typical week, which tasks take up most of your time without creating value?
Re-entering orders between the ERP and the supplier portal, every morning.
How many orders a day, and how many minutes for each one?
What teams declare, what statistics measure, what observation records. When they converge, the figure is solid; when they diverge, that is already a finding. No black box: every signal is traceable and presented in the executive committee readout.
Declared · at scale
AI agents conduct semi-structured interviews (30–45 min) with all the teams concerned: not a sample, every role. Work as it is experienced, not as it is described in a workshop.
Measured · the whole team
Five minutes, for 100% of the workforce: time split across six task families, volumes handled, perceived strain. Where the interview digs deeper, the questionnaire provides the statistics.
Observed · work sampling
Two to three one-click questions a day, for two weeks. Hundreds of observations that give the actual split of time, with its margin of error: independent of anyone’s memory.
These three sources are active from day one, without installing anything on your side. For wider scopes, two optional sources can be added via connector: process mining from your application logs and usage telemetry, enabled with your IT department’s agreement.
Five steps, from mapping real work to adoption tracked over time. Each one produces a deliverable, and each one has its own screen in your cockpit.
Five sequenced steps. Each deliverable is quantified, validated by an expert and communicated without jargon. First agent in production from week 2.
Mapping of the actual work: AI agent interviews across every team concerned. Process mining and usage telemetry as an option.
AI maturity measured across 6 dimensions, against a strict, documented scale. Results ready to present to the executive team by the end of the first week.
Use cases scored on impact × feasibility × cost. Prioritised backlog, each case argued and quantified.
A sequenced, quantified, model-agnostic roadmap that already includes your first agent in production.
Adoption, upskilling, continuous ROI tracking. And above all: change management, often the first obstacle most leadership teams face.
Built-in change management
First agent in production from week 2 on a first targeted use case, as in our reference engagement.
Explore the cockpit on a sample caseNothing reaches you without being reviewed by an expert. Here is who validates, how, what sets us apart from the alternatives, and what happens to your data.
Review is driven by risk: the AI covers the volume and self-checks routine work; the expert reads every deliverable and focuses their analysis on the high-stakes points: prioritisation, costing, roadmap. The throughput of a platform. The judgement of a senior consultant. That is what sets us apart from “AI-only” offerings.
Agent draft
The AI agent produces — Analysis at scale, structured, reproducible. Volume without compromise.
Expert review
The consultant checks — Methodological verification, sector context, anomaly detection.
Validated
Human judgement decides — The senior consultant signs off every deliverable before delivery.
Delivered to client
Nothing without validation — The client receives only deliverables that an expert has reviewed and validated.
Zero unvalidated deliverables. Every deliverable is reviewed and validated by a senior consultant before delivery.
Nothing ships without an expert’s sign-off.
Every deliverable is reviewed by the founder of SHIFTLABS, a data and AI consultant, and, depending on the scope, by a practitioner of the business function concerned, engaged per assignment and named in the proposal.
Who
The founder of SHIFTLABS, a data and AI consultant, and, depending on the scope, a practitioner of the business function concerned: finance, supply chain, data or human resources.
How
The expert is engaged per assignment, under contract, and named in the proposal: you know who reviews before you sign.
Before any delivery
Every deliverable is reviewed and signed off by its validator. Nothing is delivered without that signature.
What sets us apart
Compared with traditional consulting and 100% AI offerings, SHIFTLABS combines the throughput of agents with the judgement of an expert. Here is what that changes, in concrete terms.
The throughput of agents, the judgement of an expert.
The power of an agent platform, every deliverable reviewed by an expert who signs off. That is what consulting and AI alone cannot offer separately.
Sovereignty & compliance : CIO / DPO criteria
EU storage · Paris
Region cdg1 · AI analysis in the EU by default (Mistral, France)
Segregation by client
Access filtered by client identifier · AES-256-GCM at rest, TLS in transit
GDPR: processing governed by contract
DPA (Art. 28) available, draft version
No training on your data
SHIFTLABS’s commitment: your data is never used to train a model
A real engagement, its figures and its tipping point: what the method produces, measured rather than promised.
Case study: our first reference engagement
A firm facing high-frequency repetitive tasks. We mapped, quantified and automated: in 2 weeks, with human validation at every step.
Estimated figures, anonymised client
Timeline · 2 weeks
Agent interviews & scope framing
Mining · Costing of the 6 use cases
Build & testing of the agents in a real environment
Production rollout · Expert validation · Debrief
Estimated figures, anonymised client
6
agents in production
1,337 h
automatable / year
~€60k
estimated annual value
4 months
estimated payback
Does this scope sound familiar? We can run the same exercise on your organisation.
Discuss your scopeThe proof, quantified and grounded
Estimated figures from our first reference engagement (accounting firm, France, anonymised client). Illustrative chart, anchored on these estimates: cumulative net value would cross zero around month 4.
~€14k
Build investment
~€60k/year
Annual value identified
~4 months
Estimated payback
Locate your maturity level, choose your entry point, and start with a no-commitment diagnostic.
Tier 1
AI remains occasional, individual and ungoverned.
Tier 2
Tools help, but remain local and unshared.
Tier 3
AI supports core processes, with human review.
Tier 4
AI executes at scale; humans validate and arbitrate.
Four tiers separate isolated experimentation from the AI-native operating model. Most organisations remain on the first two: our role is to take you to the next tier, with proof.
We take you to the next tier.
Diagnosis, prioritisation, first agent in production in 2 weeks. Each step is validated by an expert.
Assess your maturity in 3 minutesA quantified-ROI pilot, a continuous platform or a performance-based model: each option is designed to reach the estimated payback, not to stretch the engagement.
Prove the value
A targeted scope to demonstrate ROI before any commitment. At a fraction of the cost of a consulting firm.
from €12 k
Scoping in 2 weeks, not several months
The pilot delivers the analysis and a first use case ready to launch in two weeks, on a targeted scope and with no follow-on commitment.
Transformation steered continuously, not a static report. Platform economics, not daily rates.
from €3.5 k
Aligned with value
For organisations with high stakes in scale and compliance. Part of the price is indexed to the value actually delivered.
On quotation
Our enterprise process
Thirty minutes to understand your context and give you a first reading of your value pools. If the potential is there, we map and quantify your use cases in the Pilot. Otherwise, you leave with a clear picture, having risked nothing.
Reply within one Paris business day
A first qualified exchange within the working day.
No commitment
A first useful insight into your value pools, even with no follow-up.
Systematic NDA
Confidentiality contractually agreed before the first exchange.
The AI analysis is carried out in the European Union by default (Mistral, France), and both the application runtime and data storage are in the Paris region. Your data is encrypted at rest (AES-256) with a key that only we hold. The exact list of our subprocessors, including countries, is published in our privacy policy and kept up to date.
Architecture: logical segregation per organisation (every access filtered by customer ID, separate files per customer), encryption in transit and at rest. Your data is never used to train a SHIFTLABS model ; the inference provider is bound by its contractual terms, referenced in the DPA.
Compliance: DPA (art. 28) available as a draft version, provided at contract signature; AI Act — transparency obligations under Article 50 applied (every interview states that it is conducted with an AI). On the Enterprise offer, Microsoft/SAML SSO, differentiated roles and reinforced isolation are scoped with your CIO and built under the contract; they are not available as standard today.
It is the first operational obstacle of any AI transformation, and we address it from the start, not at the end. Our three-step approach:
Start with one scope
Diagnostic in days. Costed roadmap. First agent deployed in 2 weeks. Every deliverable is validated by a human expert: no black box.