AI Services · Service
AI Support and Optimization
Models change every few months. Keep your prompts, connectors, agents and evaluation sets current, and keep adding use cases, with a senior team on call.
Short answer
AI support keeps your AI workflows accurate and adopted after launch: monitoring answers and usage, re-running evaluation sets when models or permissions change, tuning prompts and tool descriptions, admin support for Claude and ChatGPT workspaces, and adding new use cases from the data. It runs on a block of hours, a monthly retainer or managed services.
The launch is the easy part to plan. After it, vendors ship new models, retire features, change connectors and update pricing. Users find requests you didn't test. Without an owner, quality drifts and nobody notices until a bad answer reaches a client.
We stay on as that owner or alongside yours. Each month you get a short report: what changed, what we tested, what we fixed, and what to build next.
What a month looks like
| Activity | Cadence |
|---|---|
| Sample review of conversations and AI-written records | Weekly |
| Evaluation set re-run after any model, prompt or permission change | On change |
| Vendor release review (Anthropic, OpenAI, Salesforce, HubSpot) | Monthly |
| Usage and adoption report by team | Monthly |
| Access review of connectors and integration users | Quarterly |
| New use case scoped and built from the backlog | As hours allow |
What you get
- Named senior consultant who knows your setup
- Monitoring, evaluation re-runs and prompt tuning
- Claude and ChatGPT admin support
- Vendor change review and impact notes
- Monthly report and backlog planning
How it comes together
- Handover. We document the current setup and evaluation sets.
- Baseline. Current scores, usage and open issues.
- Run. Weekly reviews, monthly reports, fixes as needed.
- Improve. New use cases from the backlog, scored before launch.
Is this the right call?
Good fit when
- You have AI workflows in production and no one owns them full time
- You want a steady pipeline of new use cases without a new project each time
Think twice when
- Nothing is live yet; start with the readiness assessment
Mistakes we help you avoid
Judging quality from a few conversations
Use a fixed evaluation set and track the score over time.
Letting connectors pile up
Review access quarterly and remove what nobody uses.
Questions we get
Why do AI workflows need ongoing support?
Vendors change models and features often, permissions and data change, and users try new requests. Re-testing and tuning keeps answers accurate and keeps compliance comfortable.
How is support priced?
Through a block of hours, a monthly retainer or managed services. Published prices are on our support packages page.
Can you support AI tools you didn't implement?
Yes. We start with a short review of the setup and evaluation sets, then take it on.
Do you cover Agentforce and Breeze too?
Yes. The same support covers Claude, ChatGPT, Agentforce and Breeze.
Free · About 3 minutes
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