Agentforce Partner of the Year · FY26
AI agents, grounded in your data.
TrailConsult designs agent workflows, engineers the data behind them, and makes analytics conversational. Salesforce, Google Cloud, and Tableau, built by a team that stays until the numbers move.
Primary technology partners
4.75 average CSAT across 70 plus engagements, read the client references- FY26
- Partner of the Year
- 4.75
- Average CSAT
- 70+
- Engagements
- NA · EMEA
- Markets
What we do
Three services. One spine.
Agent workflows across your value chain. How you find clients, win them, and keep them, across every channel you sell and serve through.
Marketing, sales development, service, and back office. Built on Agentforce and Claude, grounded in your data, working in the channels your teams already use.
One agent converting EMEA leads in five languages
Ingestion, processing, and the modelled layer underneath everything else.
We land your source systems, build the bronze, silver, and gold tables, run the transformations, and define the semantic layer so a metric means the same thing everywhere it is used.
A reporting backlog became a plain-English question
Ask your data a question. Get an answer you can defend.
Semantic models your business agrees on, MCP connectors into your cloud data, and natural language analytics in Tableau and Tableau Next. Your teams stop queuing for reports and start asking directly.
Marketing spend traces to booked meetings
Platforms
Our primary platforms.
These are the technology partners we see success with, and the work we typically do on each.
Anthropic
Claude
Agents grounded in your own data and documents, and the reasoning layer behind the workflows we automate.
Claude Code
Engineering acceleration on pipelines, migrations, and transformations, so build work moves faster than hand-coding it.
MCP
Connectors that let a model query your governed data directly, instead of working from an export that is already out of date.
Salesforce
Partner of the Year, FY26
Agentforce
Agent workflows across marketing, sales development, service, and the back office, with guardrails and human approval wherever you need them.
Data Cloud
Structured and unstructured sources unified so agents and analytics work from the same record of truth.
Sales Cloud
Pipeline, quoting, and forecasting configured to how your business actually sells rather than how the demo org does.
Service Cloud and Field Service
Case management and field operations, including virtual remote assistance so technicians resolve issues without a truck roll.
Marketing Cloud Next
Campaign execution tied back to pipeline, so spend traces to outcomes rather than to opens.
Tableau
The reporting layer your operators live in day to day.
Data engineering
BigQuery
The warehouse most of our gold layers sit on, with bronze, silver, and gold modelled properly underneath.
dbt
Transformations and tests under version control, so the modelled layer is trusted rather than argued about.
Snowflake and Databricks
Where you already run. We meet the estate you have rather than asking you to move.
Analytics
Tableau Next
Conversational analytics on a semantic model your business agrees on.
MCP connectors
Natural language questions answered against live cloud data.
Semantic modelling
Metric definitions that mean the same thing in every dashboard, agent, and answer.
Methodology
How we deliver.
This is the delivery model behind 70 plus engagements. It is how we have repeated the same result across industries rather than starting from scratch each time.
Accelerators built from past engagements and the industry examples where we see the most value created.
You start from a baseline, not a blank page. Process designs and process maps, pre-configured Sales Cloud and pipelines, and agent skills we have already seen work. You adjust them to your requirements instead of building the same foundation from scratch for the third time.
A clear strategy and execution roadmap before the build starts. It takes risk out of implementation and gives you cost certainty across any transformation in agent workflows, data engineering, or analytics.
Carve-outs, M&A, redesigning go-to-market, or reshaping service operations. Same discipline, different scope.
Priced on outcomes, not on products delivered. Your incentives and ours are the same from day one.
Progress is measured against defined milestones, and payment follows the milestone schedule.
Managed services, but not the traditional kind. You get a point of view on what to build next, not just a queue of tickets, alongside the maintenance and support the platform actually needs to keep running.
Our forward deployed engineers work inside your team. They hold the agents, pipelines, and analytics infrastructure, ship improvements on a set cadence, and train your RevOps and data teams to run it themselves.
The work
Proof beats promises.
4.75 / 5
4.75 average CSAT across 70 plus engagements
TrailConsult did a very professional job in handling our project. They were always available and showed immense experience in handling the scale of the project.
Godreigns Amedari
Chief Operating Officer, Arnergy
Questions
Asked before the first call.
What does TrailConsult actually build?
Three things. Agent workflows across your value chain, covering marketing, sales development, service and the back office, built on Agentforce and Claude. The data engineering underneath them: ingestion, processing, and the modelled layer, with bronze, silver and gold tables on BigQuery, Data Cloud and dbt. And conversational analytics, so your teams ask a question and get an answer they can defend, on Tableau and Tableau Next with MCP connectors into your cloud data.
How do you price the work?
Against outcomes, not hours. No time and materials. We price strictly on the value and outcomes delivered, so our incentives are aligned with yours from the first day. FDE programs and enablement run capacity-based.
Do you work with private equity firms?
Yes, across the deal lifecycle. Data engineering, modeling, and hypothesis testing for underwriting and sell-side diligence. Business and technical architecture plus data migration strategy for carve-outs and M&A. Agent workflows and conversational analytics inside portfolio companies during the hold period, often with partner funding covering the pilot.
What is an FDE program?
Forward deployed engineers embedded in your team. They run your agents, pipelines, and analytics estate, and ship improvements on a cadence rather than working a ticket queue. Enablement runs alongside it: working sessions that teach your RevOps and data engineering teams to run these workflows themselves.
How fast can you deploy, and how long do your projects take?
It depends, and that is the honest answer. One client had a working agent live in four weeks on a go-to-market project. Others run forward deployed engineer programs with us that continue year over year. We size the engagement to the value it will return. If the return is a quick one, the engagement should be quick. If the value compounds over time, the program should be structured to compound with it. We would rather tell you which of those you are looking at than quote a number that fits everyone.
Where do you work?
North America and EMEA. 70 plus engagements with a 4.75 average client satisfaction score.
Private equity
Built for deal teams.
Test the thesis against the asset's own records, not the version in the CIM.
The questions that would genuinely move the price are the ones nobody can answer inside the window, because the data sits across systems nobody has modelled. We build the workload that makes the target's raw records answerable, in weeks rather than quarters.
On one catalog acquisition that meant over 300 million rows of royalty statements, and time to insight from seven days to thirteen minutes.
Shorter time to insight is not a convenience. It is pricing power.
One framework, run forward for an acquisition and in reverse for a separation.
Carve-outs fail at the boundary. The target runs on systems it does not own, the data model belongs to the parent, and the TSA has a clock on it. We agree the operating model with the sponsor before any system is touched, then land the data, name the systems of record, and sequence the cutover.
On one separation, over a million records moved in a single cutover with no rollback.
Prove it at one company, repeat it across the portfolio, and leave the asset ready to sell.
Portfolio-wide programs stall in month three, because they ask every company to change at once and none have the capacity alongside their own plan. So we start with one company and one measurable outcome, then repeat what worked. And we build toward the exit from the start, because buyers discount what they cannot verify. A quality of earnings that stalls on reconciliation, a metric defined three ways, a stack one person understands. Each one costs price, or costs certainty.
Pilots are often partner funded.
Contact
Tell us the problem. We bring the plan.
Thirty minutes, no deck. Bring the messiest thing on your desk.
- Book directly
- Calendly
- Markets
- North America and EMEA