GENERATIVE AI CONSULTING
Generative AI Consulting for B2B.Beyond the impressive demo.
Generative AI is strong at some information-heavy tasks and unreliable at others. We identify where LLMs genuinely fit the work, evaluate the output against the consequence of error and build the useful cases into controlled operations.
WHAT IT DOES WELL
What Generative AI Can Do Well in B2B
As with any AI consulting work, suitability depends on the task, source material and level of review required.
Drafting
Create useful first drafts from clear context, source material and constraints.
Extraction
Pull defined information from documents or unstructured text for downstream processing.
Summarisation
Condense meetings, documents and interactions when users can verify the important details.
Classification
Group or route text using defined categories, with evaluation against real examples.
Transformation
Reformat, translate or adapt existing material where the source and desired output are controlled.
WHERE IT FAILS
Generative AI Limitations Need to Shape the Workflow
Reliability
A fluent answer can still be wrong, incomplete or inconsistent.
Hallucination
Models can generate unsupported information, so factual use cases need grounding, evaluation and review proportionate to risk.
Cost and latency
Model choice, context size and workflow volume can materially affect operating economics and user experience.
Brand and data risk
Sensitive information, customer-facing output and regulated decisions need appropriate controls, permissions and human accountability.
FROM USE CASE TO OPERATION
Generative AI Consulting Services From Selection to Deployment
Select
Choose use cases where generative capability solves a real information problem.
Design
Define context, source material, output constraints and human responsibility.
Prototype
Test prompts, retrieval and workflow options quickly against representative examples.
Evaluate
Measure quality and failure modes rather than judging a handful of impressive outputs.
Deploy
Put the model inside the real workflow with controls, logging and escalation.
Improve
Monitor performance and change prompts, models, retrieval or process as evidence develops.
FAQ
Generative AI Consulting FAQ
What can generative AI actually do well in B2B?
Generative AI can be useful for drafting, summarisation, extraction, classification, translation and transforming information when the task has clear context and appropriate review. It is particularly helpful where people spend substantial time reading or producing text, often as one step inside broader AI workflow automation. Suitability depends on accuracy requirements, data sensitivity and the consequence of a wrong output.
Should we use ChatGPT, Claude or build our own?
The right choice depends on the workflow, data, integrations, model performance, control requirements and operating cost. A general-purpose product can be enough for individual work, while an API or custom application can fit repeatable business processes. We evaluate the job first and avoid locking the operating model to a preferred model provider, then treat rollout as an AI implementation question rather than a model-picking one.
How do we manage hallucination risk?
Manage hallucination risk by limiting the task, grounding outputs in trusted source material where appropriate, evaluating against representative examples, constraining what the model is allowed to do and keeping human review for consequential outputs. The required control should match the consequence of error. Some tasks are simply poor candidates for generative AI.
OPERATIONAL AI
Use generative AI where its strengths match the work and its failures can be controlled.
We can move from an interesting LLM demo to a production workflow that has a reason to exist.
Find the friction.
Build what helps.
Measure the change.