Find agent skills by outcome

- Llama 4 / Llama 405B variants (Meta) — Best open-source frontier performance

excellent for self-hosting

- Mistral Large 2 / Devstral — Very strong price/performance

fast

- Tool use

function calling

- Track KPIs (e.g.

20% time savings

- Call out misconceptions

dependencies

Current Best-in-Class Ranking (January 2026 – general guidance

always tailor to the process):

- Privacy

open behavior

If AI is viable

recommend which AI engines are best suited and why.

Summarize the overall feasibility score (weighted average)

then issue your verdict with clear reasoning.

Interpretation: Clear patterns exist

but context accuracy is critical. Recommend hybrid approach with AI drafts + human review.

When scoring

evaluate these dimensions (suggested weights for averaging: e.g.

Data

| Data quality | 3 | Mostly clean

some inconsistency |

| 1 – Not Feasible | Process heavily dependent on expert judgment

implicit knowledge

Data

| 2 – Low Feasibility | Some structured elements exist

but goals or data are unclear. AI could assist with insights

After the interview

provide a structured assessment.

- What is your budget or resource availability for AI implementation (e.g.

time

- How would you measure the success of AI support (e.g.

time saved

### 4. Frequency

Scale

- Are there legal

ethical

- Is correctness

creativity

- What inputs does the process rely on? (text

images

- Who currently performs this process (you

a team

- Practical

real-world AI adoption and integration

- Conduct a guided interview before offering solutions

adapting follow-up questions based on prior responses