We address the 5 challenges for companies to embrace AI
In spite of amazing potential and excitement, AI adoption in the corporate world is lagging consumer adoption: a lot of talks, limited actions, disappointing ROIs.
Blue Bridge’s closes the gap between AI value promise and corporate reality by addressing five challenges.
Challenge One
IP, data confidentiality and cyber were key concerns for scale adoption.
Blue Bridge keeps benchmark of the various models and software on those dimensions, allowing clients to make informed decisions as per their own guardrails.
Challenge Two
Models keep progressing, start-ups are mushrooming, and it is hard to tell who will win. Will Runway stay ahead of Sora, Veo and Firefly for video generation?
Will ElevenLab remain the leader in voice cloning and generation?
Will OpenAI package a zero shot OCR beating valley start-ups?
Blue Bridge updates a quality benchmark for specific use cases and calls models and SW in an agnostic way, making it easy to move from one provider to the other.
Challenge Three
Models are « up in the air », proposing their own specific UX, but most companies run a combination of SAP, Salesforce . com, ServiceNow, Docusign, MS360 and the likes. AI solutions emerge in corporate software (eg. MS Copilot, SAP's Joule or Salesforce' s Einstein) but remain siloed and don't handle specific corporate workflows.
Blue Bridge provides AI agents (replacing humans for tedious roles) and AI assistants (augmenting humans for complex decision-making or creative activities) fluidly cutting across corporate systems.
Challenge Four
Generative AI is not the solution to every problem. Hallucinations and approximations were concerns.
Blue Bridge is assembling ad’ hoc pipelines of technologies, combining rule-based / deterministic algorithms with machine learning / probabilistic approaches to «do the job».
The purpose is not to deploy a given technology but to deliver the best outcome. For instance, insurance claims handling combines a deterministic approach (automatically interpreting policies) and a probabilistic one (based on previous human claims handling), with human learning reinforcement (for complex cases). A performing RAG articulates strong indexation and corporate search engine with an LLM for knowledge metabolization.
Challenge Five
Classic person-day-based system integration usually destroys the ROI.
Blue Bridge put AI automation at the heart of its integration platform « plugging » AI solutions into corporate workflows. Our platform comprises automated tools (eg. process mapping and diagnosis), predefined agents /assistants for front and back office or supply chain use cases (which underlying models can be interchanged) and a collaborative methodology involving clients business / support and IT functions. We charge per AI agent / AI assistant deployed or when reaching certain quantitative KPIs when agreeable ; we do not charge per person x days.