Beyond call recording: getting real ROI from Gong
Most teams treat Gong as expensive call storage. The return is in coaching, deal execution, and forecast accuracy. Here is how to move from recording to results.
Read the full post → What You Get
The outcomes a strong ai & technology consulting engagement delivers.
Vendor-neutral guidance from senior consultants and AI engineers
Production AI, not pilots that never ship
Avoid expensive mistakes before contracts are signed
Outcomes measured in revenue, time saved, and risk reduced
Clear technology and AI roadmaps tied to business strategy
Governance, accuracy, and human-in-the-loop built in
How We Work
The engagement model.
Predictable phases. Clear deliverables. No surprises.
01
Discovery
One to two working sessions to map your current state, business goals, gaps, and constraints. We come out with a written scope document and recommendation.
02
Design
Documented solution architecture, realistic timeline, and a transparent commercial proposal. No surprises and no hidden scope.
03
Build
Configuration, development, integrations, data migration, and QA, with weekly demos, regular client touchpoints, and on-the-fly adjustments.
04
Launch & Optimize
Training, change management, hypercare, and ongoing optimization. We do not disappear at go-live, we stick around until success metrics are confirmed.
Common Challenges
What we see over and over in ai & technology consulting engagements.
The challenges that come up in nearly every conversation we have with clients about ai & technology consulting.
A backlog of AI pilots, few in production
Industry research shows most enterprise AI initiatives stall before production. The bottleneck is rarely the model, it is governance, change management, evaluation, and integration with real workflows.
Leadership uncertainty on where to bet
Every vendor pitches AI. The question leaders need answered is where AI will create durable advantage in their business, and where it will produce expensive parity.
Existing platform investments to leverage
Salesforce, Microsoft, Google, and AWS all have credible AI platforms. So do Anthropic and OpenAI. The right answer usually combines them, and depends on the workflow, not the vendor.
Data and identity readiness for AI
AI is only as good as the data it can see and act on. Most companies are an identity, data quality, and access management project away from being able to deploy AI safely.
Risk, governance, and regulatory pressure
The EU AI Act, NIST AI RMF, ISO 42001, and emerging state laws are reshaping how enterprises must govern AI. Most companies have not yet built the muscle.
Build vs. buy across the AI stack
Foundation models, agent frameworks, vector databases, evaluation platforms, every layer has both a buy and build option. Picking right requires real engineering judgment.
Practice Areas
The major ai & technology consulting sub-practices we deliver.
Each represents a deep specialization with dedicated playbooks, accelerators, and experienced practitioners.
AI Strategy & Roadmapping
A structured engagement to map where AI will create the most value in your business, and produce a sequenced, accountable roadmap with measurable outcomes.
AI Governance Programs
AI inventory, risk classification, approval workflows, monitoring, and audit-ready evidence aligned to NIST AI RMF, ISO 42001, and EU AI Act.
Agentic AI & Copilots
Production agent architectures using Claude, GPT-4, Agentforce, and custom frameworks. Tool use, evaluation, human-in-the-loop, and escalation patterns.
RAG & Knowledge Architectures
Retrieval-augmented generation systems built for the realities of enterprise knowledge, ingestion, chunking, embeddings, retrieval, evaluation, and operations.
Platform Selection & Architecture
Independent assessment and recommendation across Salesforce Agentforce, Microsoft Copilot, Google Vertex AI, AWS Bedrock, and direct foundation model APIs.
Technology Consulting (non-AI)
Architecture review, vendor selection, M&A integration planning, platform consolidation, and digital transformation strategy.
What We Deliver
Concrete deliverables, not slide decks.
Every engagement produces working artifacts your team can use long after we leave.
AI strategy and roadmap documents
AI maturity diagnostic and gap analysis
AI governance framework (NIST AI RMF, ISO 42001 aligned)
Production AI agents (Claude, GPT-4, Agentforce, custom)
RAG architectures and knowledge platforms
AI evaluation and observability infrastructure
Platform selection and vendor assessment
Architecture review and modernization plans
M&A technology due diligence and integration plans
Executive AI fluency workshops
Platforms & Ecosystem
The technology we typically deploy.
We are platform-neutral and pick what fits, but here are the tools where our team carries deep, hands-on certification.
Anthropic Claude (API, Bedrock, Vertex)
OpenAI / Azure OpenAI
AWS Bedrock
Google Vertex AI
Salesforce Agentforce
Microsoft Copilot Studio
LangChain / LangSmith
LlamaIndex
Pinecone
Weaviate
pgvector
Databricks Mosaic
Hugging Face
Vellum
Humanloop
Arize
Fiddler
Snowflake Cortex
Cohere
Outcomes We Deliver
The metrics we actually move.
Engagements are measured by movement on the numbers that matter. These are the directions of travel we commit to.
AI pilot to production rate
Increased
Time saved per knowledge worker
Faster
AI workflow accuracy
Improved
AI governance findings
Reduce to zero material
Time to ROI on AI investment
Faster
Employee AI adoption rate
Increased
Signature Frameworks
Proprietary methodologies for ai & technology consulting work.
Every engagement leverages reusable assets, frameworks, blueprints, and diagnostics built up over hundreds of client projects.
AI Maturity Diagnostic
Our two-week assessment that maps where AI will and will not create value in your organization, plus a sequenced roadmap with measurable outcomes.
AI Governance Operating Model
A framework for AI inventory, risk classification, approval workflows, and ongoing monitoring that scales beyond a single steering committee.
RAG Reference Architecture
A battle-tested pattern for retrieval-augmented generation in enterprise, covering ingestion, chunking, embeddings, retrieval, and evaluation.
AI Agent Design Method
Our approach to designing AI agents that handle real work, tool use, error handling, escalation paths, and human-in-the-loop workflows.
Industries Served
Where this capability shows up.
AI & Technology Consulting engagements run across regulated and complex industries. Each combines this capability with sector-specific expertise and regulatory awareness.
Case Studies
Recent ai & technology consulting work.
Financial Services — Lending
A business lender processing 24,000 leads a month built AI lead scoring and a Data Cloud roadmap to protect a limited sales team
A lender receiving 24,000 leads a month — of which only 400 completed an application — needed scoring and AI agents so a limited sales team could focus on the best prospects.
Read the case study → BiotechnologyA biotech startup cut support time 30% with Service Cloud AI agents and MuleSoft integration
A fast-growing synthetic-DNA manufacturer used Service Cloud, Agentforce, and MuleSoft to absorb rising support volume without adding headcount.
Read the case study → Telecommunications & InfrastructureA telecom-infrastructure contractor used Document AI and Agentforce to read forms its existing tools could not
A tower-construction company automated extraction of checkbox-heavy inspection forms and added natural-language project analysis after spending 60+ hours failing to do it alone.
Read the case study →Featured Insight
Insight & analysis from our ai & technology consulting team.
Practitioner-level analysis from the consultants delivering the work.
Revenue Operations
Frequently Asked
Common questions about ai & technology consulting.
Are you locked into a particular AI vendor?
No. We are an Anthropic Build Partner, run heavy work in Bedrock and Vertex, and deploy across Salesforce Agentforce, Microsoft Copilot, and direct model APIs. The right answer depends on the workflow, not the vendor.
How do we know AI will actually pay back?
Every AI engagement starts by identifying the specific workflows, hours, or revenue movements we expect to influence, and how we will measure them. If we cannot articulate the measurement plan, we do not start the work.
What about model risk and governance?
Governance is the work, not an afterthought. We deliver AI engagements with governance evidence built in, inventory, classification, approval, monitoring, and audit trails, aligned to NIST AI RMF and emerging regulation.
Can you help us decide what to build vs. what to buy?
Yes, this is one of our most-requested engagements. We deliver a structured assessment, sized for your team, that maps the major build / buy decisions and gives a defensible recommendation for each.
Explore More
Other capabilities at Abstrakt Solutions.
Custom Development
Custom applications, platform extensions, integrations, and engineered solutions built when off-the-shelf software won't fit.
Learn more →Revenue Operations
Align marketing, sales, and customer success into one revenue engine. Process, forecasting, attribution, and tech-stack optimization.
Learn more →